All Publications

Journal Publications: 

1. K. G. Begum,  R. Ramanan, V. B. S. Prasath. Explainable machine learning for predictive analysis of thyroid disorders. Multimedia Tools and Applications, 2024. doi:TBA

2. H. Aetesam, S. K. Maji, V. B. S. Prasath. Hyperspectral image restoration using noise gradient and dual priors under mixed noise conditions. CAAI Transactions on Intelligence Technology, 2024. doi:10.1049/cit2.12355

3. P. Rajdeo, B. Aronow, V. B. S. Prasath. Deep learning-based multimodal spatial transcriptomics analysis for cancer. Advances in Cancer Research, vol 163, July 2024. doi:10.1016/bs.acr.2024.08.001.

4. S. Singh, H. Jadli, R. P. Priya, V. B. S. Prasath. KDTL: Knowledge-distilled transfer learning framework for diagnosing mental disorders using EEG spectrograms. Neural Computing and Applications, 36(30), 18919-18934, October 2024. doi:10.1007/s00521-024-10207-0

5. R. Nakagaki, S. S. Debsarkar, H. Kawanaka, B. Aronow, V. B. S. Prasath. Deep learning-based IDH1 gene mutation prediction using histopathological imaging and clinical data. Computers in Biology and Medicine, 179, 108902, September 2024. doi:10.1016/j.compbiomed.2024.108902

6. N. Salamat, M. M. S. Missen, N. Akhtar, M. Mustahsan, V. B. S. Prasath. Color image restoration by filtering methods: A review. Soft Computing,  28 (13-14), 7755–7782, July 2024. doi:10.1007/s00500-024-09673-4

7. X. Liu, S. Prasath, I. Siddiqui, T. Walters, L. A Denson, PROTECT consortium, J. Dhaliwal. Machine learning-based prediction of pediatric ulcerative colitis treatment response using diagnostic histopathology. Gastroenterology, 166(5), 921-924, May 2024. doi:10.1053/j.gastro.2024.01.033

8. X. Liu, J. Reigle, V. B. S. Prasath, J. Dhaliwal. Artificial intelligence image-based prediction models in IBD exhibit high risk of bias: A systematic review. Computers in Biology and Medicine, 171, 108093, March 2024. doi:10.1016/j.compbiomed.2024.108093

9. E. G. Zarajabad, P. D. Grimm, B. Saremi, J. Wang, S. A. Ahmad, S. A. Shah, R. C. Quillin III, S. H. Patel, A. J. Knapp, V. B. S. Prasath, T. D. Mast. Deep learning-enhanced 3D echo decorrelation imaging for monitoring radiofrequency ablation in ex vivo human liver. Proceedings of Meetings on Acoustics (POMA), 51(1), February 2024. doi:10.1121/2.0001821

10. N. Gaddis, J. Fortriede, M. Guo, E. E. Bardes, M. Kouril, S. Tabar, K. Burns, M. E. Ardini-Poleske, S. Loos, D. Schnell, K. Jin, B. Iyer, Y. Du, B.-X. Huo, A. Bhattacharjee, J. Korte, R. Munshi, V. Smith, A. Herbst, J. A. Kitzmiller, G. C. Clair, J. Carson, J. Adkins, E. E. Morrisey, G. S. Pryhuber, R. Misra, J. A. Whitsett, X. Sun, T. Heathorn, B. Paten, V. B. S. Prasath, Y. Xu, T. Tickle, B. J. Aronow, N. Salomonis. LungMAP portal ecosystem: Systems-level exploration of the lung. American Journal of Respiratory Cell and Molecular Biology, 129-139, 70(2) February 2024. doi:10.1165/rcmb.2022-0165OC 

11. M. Arshad, A. M. Qamar, M. M. S. Missen, A. A. Lodhi, V. B. S. Prasath. Global trends and collaborations in dengue virus research: A scientometric and bibliometric overview (1872–2019). International Journal of Design & Nature and Ecodynamics, 1539-1548, 18(6), December 2023. doi:10.18280/ijdne.180630

12. S. Shamin, M. M. S. Missen, A. M. Qamar, A. Firdous, Q. U. Ain, V. B. S. Prasath. Global trends in poliomyelitis research: A bibliometric analysis from 1857-2019. International Journal of Design & Nature and Ecodynamics, 1333-1346, 18(6) December 2023. doi:10.18280/ijdne.180606

13. A. Gundawar, S. Lodha, V. Vijayarajan, B. Iyer, V. B. S. Prasath. On the performance of new higher order transformation functions for highly efficient dense layers. Neural Processing Letters, 55(8), 10655-10668, December 2023. doi:10.1007/s11063-023-11343-9

14. P. Satti, V. Shrotriya, B. Garg, V. B. S. Prasath. DIBS: Distance- and intensity-based separation filter for high-density impulse noise removal. Signal, Image and Video Processing, 17(8), 4181-4188, November 2023. doi:10.1007/s11760-023-02650-8

15. K. Medichalam, V. Vijayarajan, V. Kumar, I. M. Iyer, Y. K. Vanukuri, V. B. S. Prasath, B. Swapna. Trustworthy artificial intelligence and automatic Morse code based communication recognition with eye tracking. Journal of Mobile Multimedia, 19(06), 1439-1462, October 2023. doi:10.13052/jmm1550-4646.1964 (AI India News)

16. P.-J. Van Camp, V. B. S. Prasath, D. B. Haslam, A. Porollo. MGS2AMR: A gene-centric mining of metagenomic sequencing data for pathogens and their antimicrobial resistance profile. Microbiome, 11, Article number 223, October 2023. doi:10.1186/s40168-023-01674-z

17. P. V. S. P. Raghavendra, C. Charitha, K. G. Begum, V. B. S. Prasath. Deep learning-based skin lesion multi-class classification with global average pooling improvement. Journal of Digital Imaging, 36(5), 2227-2248, October 2023. doi:10.1007/s10278-023-00862-5.

18. E. H. S. Diop, A. Ngom, V. B. S. Prasath. Signal approximations based on an nonlinear and optimal piecewise affine functions. Circuits, Systems, and Signal Processing, 42(4), 2366-2384, April 2023. doi:10.1007/s00034-022-02224-y

19. S. Boopathiraja, P. Kalavathi, S. Deoghare, V. B. S. Prasath. Near lossless compression for 3D radiological images using optimal multilinear singular value decomposition (3D-VOI-OMLSVD). Journal of Digital Imaging, 36(1), 259-275, February 2023. doi:10.1007/s10278-022-00687-8

20. T. A Cazares, F. W. Rizvi, B. Iyer, X. Chen, M. Kotliar, J. A. Wayman, A. Bejjani, O. Donmez, B. Wronowski, S. Parameswaran, L. C. Kottyan, A. Barski, M. T. Weirauch, V. B. S. Prasath, E. R. Miraldi. maxATAC: genome-scale transcription-factor binding prediction from ATAC-seq with deep neural networks. PLOS Computational Biology, 19(1), e1010863, January 2023. doi:10.1371/journal.pcbi.1010863

21. G. Li, B. Song, H. Singh, V. B. S. Prasath, H. L. Grimes, N. Salomonis. Decision level integration of unimodal and multimodal single cell data with scTriangulate. Nature Communications, 14, 406, January 2023. doi:10.1038/s41467-023-36016-y

22. M. Shah, D. Jain, V. B. S. Prasath, K. Dufendach. Artificial intelligence in bronchopulmonary dysplasia - Current research and unexplored frontiers. Pediatric Research, 93(2), 287-290, January 2023. doi:10.1038/s41390-022-02387-z

23. N. Salamat, A. H. Arif, M. Mustahsan, M. M. S. Missen, V. B. S. Prasath. On compacton traveling wave solutions of Zakharov-Kuznetsov-Benjamin-Bona-Mahony (ZK-BBM) equation. Computational and Applied Mathematics, 41(8), Article ID 365, December 2022. doi:10.1007/s40314-022-02082-z

24. K. Jin, D. Schnell, G. Li, N. Salomonis, S. Prasath, R. Szczesniak, B. J. Aronow. CellDrift: Inferring perturbation responses in temporally sampled single-cell data. Briefings in Bioinformatics, 23(5), 1-11, September 2022. doi:10.1093/bib/bbac324

25. A. B. A. Hassanat, A. A. Albustanji, A. S. Tarawneh, M. Alrashidi, H. Alharbi, M. Alanazi, M. Alghamdi, I. S. Alkhazi, V. B. S. Prasath. DeepVeil: Deep learning for identification of face, gender, expression recognition under veiled conditions. International Journal of Biometrics, 14(3/4), 453-480, August 2022. doi:10.1504/IJBM.2022.10048981

26. S. Bharati, P. Podder, D. N. H. Thanh, V. B. S. Prasath. Dementia classification using MR imaging and voting based machine learning models. Multimedia Tools and Applications, 81(18), 25971-25992, July 2022. doi:10.1007/s11042-022-12754-x

27. S. Bharati, M. R. H. Mondal, P. Podder, V. B. S. Prasath. Federated learning: Applications, challenges and future directions. International Journal of Hybrid Intelligent Systems, 18(1-2), 19-35, May 2022. doi:10.3233/HIS-220006

28. S. Bharati, M. R. H. Mondal, P. Podder, V. B. S. Prasath. Deep learning for medical image registration: A comprehensive review. International Journal of Computer Information Systems and Industrial Management Applications, 14, 173-190, April 2022. doi:Weblink

29. D. Katsuma, H. Kawanaka, V. B. S. Prasath, B. J. Aronow. Data augmentation using generative adversarial networks for multi-class segmentation of lung confocal IF images. Journal of Advanced Computational Intelligence and Intelligent Informatics, 26(2), 138-146, March 2022. doi:10.20965/jaciii.2022.p0138

30. S. Boopathiraja, V. Punitha, P. Kalavathi, V. B. S. Prasath. Computational 2D and 3D medical image data compression models. Archives of Computational Methods in Engineering, 29(2), 975-1007, March 2022. doi:10.1007/s11831-021-09602-w

31. D. N. H. Thanh, L. T. Thanh, U. Erkan, A. Khamparia, V. B. S. Prasath. Dermoscopic image segmentation method based on convolutional neural networks. International Journal of Computer Applications in Technology, 66(2), 89-99, December 2021. doi:10.1504/IJCAT.2021.119757

32. N. Salamat, M. M. S. Missen, V. B. S. Prasath. Recent developments in computational color image denoising with PDEs to deep learning: A review. Artificial Intelligence Review, 54(8), 6245-6276, December 2021. doi:10.1007/s10462-021-09977-z

33. G. Li, B. Iyer, V. B. S. Prasath, Y. Ni, N. Salomonis. DeepImmuno: Deep learning-empowered prediction and generation of immunogenic peptides for T-cell immunity. Briefings in Bioinformatics, 22(6), 1-16, November 2021. doi:10.1093/bib/bbab160

34. D. N. H. Thanh, V. B. S. Prasath, T. K. Phung, N. Q. Hung. Impulse denoising based on noise accumulation and harmonic analysis techniques. Optik - International Journal for Light and Electron Optics, 241, Article ID 166163, September 2021. doi:10.1016/j.ijleo.2020.166163

35. M. Shah, D. Shu, V. B. S. Prasath, Y. Ni, A. Schapiro, K. Dufendach. Machine learning for detection of correct peripherally inserted central catheter tip position from radiology reports in infants. Applied Clinical Informatics, 12(04), 856-863, August 2021. doi:10.1055/s-0041-1735178

36. S. Boopathiraja, P. Kalavathi, V. B. S. Prasath. On a hybrid lossless compression technique for three-dimensional medical images. Journal of Applied Clinical Medical Physics, 22(8), 191-203, August 2021. doi:10.1002/ACM2.12960

37. T. Priya, P. Kalavathi, V. B. S. Prasath, R. Sivanesan. Brain tissue volume estimation to detect Alzheimer’s disease in magnetic resonance images. Soft Computing, 25(15), 10007-10017, August 2021. doi:10.1007/s00500-021-05621-8

38. M. Husnain, M. M. S. Missen, N. Akhtar, M. Coustaty, S. Mumtaz, V. B. S. Prasath. A systematic study on the role of SentiWordNet in opinion mining. Frontiers of Computer Science, 15(5), Article ID 154614, August 2021. doi:10.1007/s11704-019-9094-0

39. S. Bharati, P. Podder, M. R. H. Mondal, V. B. S. Prasath. Medical imaging with deep learning for COVID-19 diagnosis: A comprehensive review. International Journal of Computer Information Systems and Industrial Management Applications, 13, 91-112, July 2021. doi:Weblink

40. S. Bharati, P. Podder, M. R. H. Mondal, V. B. S. Prasath. CO-ResNet: Optimized ResNet model for COVID-19 diagnosis from X-ray images. International Journal of Hybrid Intelligent Systems, 17(1-2), 71-85, July 2021. doi:10.3233/HIS-210008

41. R. Deotale, S. Rawat, V. Vijayarajan, V. B. S. Prasath. POCASUM: Policy categorizer and summarizer based on text mining and machine learning. Soft Computing, 25(14), 9365-9375, July 2021. doi:10.1007/s00500-021-05916-w

42. V. B. S. Prasath, D. N. H. Thanh, L. M. Hieu, L. T. Thanh. Compression artifacts reduction with multiscale tensor regularization. Multidimensional Systems and Signal Processing, 32(2), 521-531, April 2021. doi:10.1007/s11045-020-00747-8

43. J. Zhang, Q. Wu, C. B. Johnson, G. Pham, J. M. Kinder, A. Olsson, A. Slaughter, M. May, B. Weinhaus, A. D'Alessandro, J. D. Engel, J. X. Jiang, J. M. Kofron, L. F. Huang, V. B. S. Prasath, S. S. Way, N. Salomonis, H. L. Grimes, D. Lucas. In situ mapping identifies distinct vascular niches for myelopoiesis. Nature, 590, 457-462, February 2021. doi:10.1038/s41586-021-03201-2

44. M. M. S. Missen, A. Naeem, H. Asmat, N. Salamat, N. Akhtar, M. Coustaty, V. B. S. Prasath. Improving seller-customer communication process using word embeddings. Journal of Ambient Intelligence and Humanized Computing, 12(2), 2257-2272, February 2021. doi:10.1007/s12652-020-02323-1

45. D. N. H. Thanh, N. H. Hai, L. M. Hieu, P. Tiwari, V. B. S. Prasath. Skin lesion segmentation method for dermoscopic images with convolutional neural networks and semantic segmentation. Computer Optics, 45(1), 122-129, January 2021. doi:10.18287/2412-6179-CO-748

46. T. Hayakawa, V. B. S. Prasath, H. Kawanaka, B. J. Aronow, S. Tsuruoka. Computational nuclei segmentation methods in digital pathology: A survey. Archives of Computational Methods in Engineering, 28(1), 1-13, January 2021. doi:10.1007/s11831-019-09366-4

47. D. N. H. Thanh, V. B. S. Prasath, S. Dvoenko, L. M. Hieu. An adaptive image inpainting method based on Euler’s elastica with adaptive parameters estimation and the discrete gradient method. Signal Processing, 178, 107797, January 2021. doi:10.1016/j.sigpro.2020.107797

48. D. N. H. Thanh, V. B. S. Prasath, L. M. Hieu, S. Dvoenko. An adaptive method for image restoration based on high-order total variation and inverse gradient. Signal, Image and Video Processing, 14(6), 1189-1197, September 2020. doi:10.1007/s11760-020-01657-9

49. A. Rashid, N. Salamat, V. B. S. Prasath. Dynamic increased capacity approach steganography in spatial domain. Traitement du Signal, 37(4), 671-678, August 2020. doi:10.18280/ts.370417

50. V. B. S. Prasath, D. N. H. Thanh, N. Q. Hung, L. M. Hieu. Multiscale gradient maps augmented Fisher information-based image edge detection. IEEE Access, 8, 141104-141110, August 2020. doi:10.1109/ACCESS.2020.3013888

51. D. N. H. Thanh, N. H. Hai, V. B. S. Prasath, L. M. Hieu, J. M. R. S. Tavares. A two-stage filter for high density salt and pepper denoising. Multimedia Tools and Applications, 79(29-30), 21013-21035, August 2020. doi:10.1007/s11042-020-08887-6

52. V. B. S. Prasath, D. N. H. Thanh, L. T. Thanh, N. Q. San, S. Dvoenko. Human visual system consistent model for wireless capsule endoscopy image enhancement and applications. Pattern Recognition and Image Analysis, 30(3), 280-287, July 2020. doi:10.1134/S1054661820030219

53. D. N. H. Thanh, V. B. S. Prasath, L. M. Hieu, N. N. Hien. Melanoma skin cancer detection method based on adaptive principal curvature, colour normalisation and feature extraction with the ABCD rule. Journal of Digital Imaging, 33(3), 574-585, June 2020. doi:10.1007/s10278-019-00316-x

54. E. H. S. Diop, A.-O. Boudraa, V. B. S. Prasath. Optimal nonlinear signal approximations based on piecewise constant functions. Circuits, Systems and Signal Processing, 39(5), 2673-2694, May 2020. doi:10.1007/s00034-019-01285-w 

55. L. M. Hieu, D. N. H. Thanh, V. B. S. Prasath. Second order monotone difference schemes with approximation on non-uniform grids for two-dimensional quasilinear parabolic convection-diffusion equations. Vestnik St. Petersburg University, Mathematics, 53(2), 232-240, April 2020. doi:10.1134/S1063454120020107

56. D. N. H. Thanh, L. T. Thanh, N. N. Hien, S. Prasath. Adaptive total variation L1 regularization for salt and pepper image denoising. Optik - International Journal for Light and Electron Optics, 208, Article ID 163677, April 2020. doi:10.1016/j.ijleo.2019.163677

57. M. Singh, U. Bajpai, V. Vijayarajan, V. B. S. Prasath. Generation of fashionable clothes using generative adversarial networks: A preliminary feasibility study. International Journal of Clothing Science and Technology, 32(2), 177-187, April 2020. doi:10.1108/IJCST-12-2018-0148

58. M. M. S. Missen, S. Qureshi, N. Salamat, N. Akhtar, H. Asmat, M. Coustaty, V. B. S. Prasath. Scientometric analysis of social science and science disciplines in a developing nation. Scientometrics, 123, 113–142, April 2020. doi:10.1007/s11192-020-03379-8

59. S. Bidani, R. P. Priya, V. Vijayarajan, V. B. S. Prasath. Automatic body mass index detection using correlation of face visual cues. Technology and Health Care, 28(1), 107-112, January 2020. doi:10.3233/THC-191850

60. A. B. Hassanat, K. Almohammadi, E. Alkafaween, E. Abunawas, A. Hammouri, V. B. S. Prasath. Choosing mutation and crossover ratios for genetic algorithms - A review with a new dynamic approach. Information, 10(12), 390, December 2019. doi:10.3390/info10120390

61. M. M. S. Missen, A. Javed, H. Asmat, M. Nosheen, M. Coustaty, N. Salamat, V. B. S. Prasath. Systematic review and usability evaluation of writing mobile apps for children. New Review of Hypermedia and Multimedia, 25(3), 137-160, December 2019. Special issue on Advances in Multimedia and Educational Technology. doi:10.1080/13614568.2019.1677787

62. N. H. Hai, L. M. Hieu, D. N. H. Thanh, N. V. Son, V. B. S. Prasath. An adaptive image inpainting method based on the weighted mean. Informatica, 43(4), 503-513, December 2019. doi:10.31449/inf.v43i4.2461

63. H. A. A. Alfeilat, A. B. A. Hassanat, O. Lasassmeh, A. S. Tarawneh, M. B. Alhasanat, H. S. E. Salman, V. B. S. Prasath. Effects of distance measure choice on K-nearest neighbor classifier performance: A review. Big Data, 7(4), 221-248, December 2019. doi:10.1089/big.2018.0175

64. V. B. S. Prasath, R. Pelapur, G. Seetharaman, K. Palaniappan. Multiscale structure tensor for improved feature extraction and image regularization. IEEE Transactions on Image Processing, 28(12), 6198-6210, December 2019. doi:10.1109/TIP.2019.2924799

65. A. Pranav, R. Rajeshkannan, V. Vijayarajan, V. B. S. Prasath. Break, Make, and Take: An information retrieval approach. Sādhanā, 44, 204, 11pp, September 2019. doi:10.1007/s12046-019-1187-9

66. S. M. H. Mousavi, V. Lyashenko, V. B. S. Prasath. Analysis of a robust edge detection system in different color spaces using color and depth images. Computer Optics, 43(4), 632-646, July 2019. doi:10.18287/2412-6179-2019-43-4-632-646

67. D. N. H. Thanh, V. B. S. Prasath, L. M. Hieu. A review on CT and X-ray images denoising methods. Informatica, 43(2), 151-159, June 2019. doi:10.31449/inf.v43i2.2179

68. V. B. S. Prasath. Video denoising with adaptive temporal averaging. Engineering Reviews, 39(3), 243-247, June 2019. doi:10.30765/er.39.3.05

69. D. N. H. Thanh, V. B. S. Prasath, N. V. Son, L. M. Hieu. An adaptive image inpainting method based on the modified Mumford-Shah model and multiscale parameter estimation. Computer Optics, 43(2), 251-257, May 2019. doi:10.18287/2412-6179-2019-43-2-251-257

70. M. Attik, M. M. S. Missen, M. Coustaty, G. S. Choi, F. S. Alotaibi, N. Akhtar, M. Z. Jhandir, V. B. S. Prasath, N. Salamat, M. Husnain. OpinionML - Opinion markup language for sentiment representation. Symmetry, 11(4), 545, April 2019. doi:10.3390/sym11040545

71. V. B. S. Prasath, D. N. H. Thanh. Structure tensor adaptive total variation for image restoration. Turkish Journal of Electrical Engineering and Computer Sciences, 27(2), 1147-1156, March 2019. doi:10.3906/elk-1802-76

72. S. P. Gochhayat, P. Kaliyar, M. Conti, P. Tiwari, V. B. S. Prasath, D. Gupta, A. Khanna. LISA: Lightweight context-aware IoT service architecture. Journal of Cleaner Production, 212, 1345-1356, March 2019. doi:10.1016/j.jclepro.2018.12.096

73. A. B. Hassanat, V. B. S. Prasath, M. Al-kasassbeh, A. S. Tarawneh, A. J. Al-shamailh. Magnetic energy-based feature extraction for low-quality fingerprint images. Signal, Image and Video Processing, 12(8), 1471-1478, November 2018. doi:10.1007/s11760-018-1302-0

74. A. B. Hassanat, G. Altarawneh, A. S. Tarawneh, H. Faris, M. B. Alhasanat, A. De Voogt, B. Al-Rawashdeh, M. Alshamaileh, V. B. S. Prasath. On computerizing the ancient game of tab. International Journal of Gaming and Computer-Mediated Simulations (IJGCMS), 10(3), Article 2, 21pp, September 2018. doi:10.4018/IJGCMS.2018070102 

75. A. Yonekura, H. Kawanaka, V. B. S. Prasath, B. J. Aronow, H. Takase. Automatic disease stage classification of glioblastoma multiforme histopathological images using deep convolutional neural network. Biomedical Engineering Letters, 8(3), 321-327, August 2018. doi:10.1007/s13534-018-0077-0

76. A. B. Hassanat, V. B. S. Prasath, M. A. Abbadi, S. A. Abu-Qdari, H. Faris. An improved genetic algorithm with a new initialization mechanism based on regression techniques. Information, 9(7), 167, July 2018. doi:10.3390/info9070167

77. V. B. S. Prasath. Automatic image and video analysis for capsule endoscopy - An open frontier. International Journal of Robotic Engineering, 3(1), 007, June 2018. Invited paper. doi:10.35840/2631-5106/4107

78. V. B. S. Prasath, J. C. Moreno. On convergent finite difference schemes for variational - PDE based image processing. Computational and Applied Mathematics, 37(2), 1562-1580, May 2018. doi:10.1007/s40314-016-0414-9

79. M. M. S. Missen, M. Coustaty, N. Salamat, V. B. S. Prasath. SentiML++: An extension of the SentiML sentiment annotation scheme. New Review of Hypermedia and Multimedia, 24(1), 28-43, March 2018. doi:10.1080/13614568.2018.1448007

80. V. B. S. Prasath, D. Vorotnikov. On time adaptive critical variable exponent vectorial diffusion flows and their applications in image processing I. Analysis. Nonlinear Analysis, 168, 176-197, March 2018. doi:10.1016/j.na.2017.11.013

81. A. Rashid, N. Salamat, V. B. S. Prasath. An algorithm for data hiding in radiographic images and ePHI/R application. Technologies, 6(1), 7, March 2018. Special issue on Medical Imaging & Image Processing II. doi:10.3390/technologies6010007

82. V. B. S. Prasath. Deep learning based computer-aided diagnosis for neuroimaging data: Focused review and future potential. Neuroimmunology and Neuroinflammation, 5(1), 3pp, January 2018. Invited paper. doi:10.20517/2347-8659.2017.68

83. D. Sharma, V. B. S. Prasath, V. Vijayarajan, M. Kubendiran, R. Padmapriya. Enhanced multi-view point non-negative matrix factorization clustering for clinical documents analysis. Biomedical and Pharmacology Journal, 10(4), 2135-2143, December 2017. doi:10.13005/bpj/1338

84. L. Chen, V. B. S. Prasath. Measuring bone density connectivity using dual energy X-ray absorptiometry images. International Journal of Fuzzy Logic and Intelligent Systems, 17(4), 235-244, December 2017. doi:10.5391/IJFIS.2017.17.4.235

85. V. B. S. Prasath. Image denoising by anisotropic diffusion with inter-scale information fusion. Pattern Recognition and Image Analysis, 27(4), 748-753, September 2017. doi:10.1134/S1054661817040174

86. A. B. Hassanat, V. B. S. Prasath, B. M. Al-Mahadeen, S. M. M. Alhasanat. Classification and gender recognition from veiled-faces. International Journal of Biometrics, 9(4), 347-364, September 2017. doi:10.1504/IJBM.2017.10009351

87. V. B. S. Prasath. Quantum noise removal in X-ray images with adaptive total variation regularization. Informatica, 28(3), 505-515, September 2017. doi:10.15388/Informatica.2017.141

88. P. Kalavathi, M. Senthamilselvi, V. B. S. Prasath. Review of computational methods on brain symmetric and asymmetric analysis from neuroimaging techniques. Technologies, 5(2), 16, June 2017. Special issue on Medical Imaging & Image Processing II. doi:10.3390/technologies5020016

89. H. Aliakbarpour, J. F. Ferreira, V. B. S. Prasath, K. Palaniappan, G. Seetharaman, J. Dias. A probabilistic framework for 3D reconstruction using heterogeneous sensors. IEEE Sensors Journal, 17(9), 2640-2641, May 2017. doi:10.1109/JSEN.2017.2679187

90. V. B. S. Prasath. Tensor sketch - Scene sketch generation using structure tensor. Asian Journal of Physics, 26(3-4), 213-218, April 2017. Special issue on Trends in Image Processing and Machine Learning. Invited paper.

91. V. B. S. Prasath. Vascularization from Flexible Imaging Color Enhancement (FICE) for polyp localization. Journal of Medicine and Life, 10(2), 147-149, April 2017. doi:Weblink

92. V. B. S. Prasath. App review series: Radiology Pocket Game. Journal of Digital Imaging, 30(2), 127-129, April 2017. doi:10.1007/s10278-016-9924-7 

93. A. B. Hassanat, V. B. S. Prasath, K. I. Mseidein, M. Al-awadi, A. M. Hammouri. A hybrid wavelet-shearlet approach to robust digital image watermarking. Informatica, 41(1), 3-24, March 2017. Special issue on End-user Privacy, Security, and Copyright issues. doi:Weblink

94. V. B. S. Prasath. Polyp detection and segmentation from video capsule endoscopy: A review. Journal of Imaging, 3(1), 15pp, March 2017. Special issue on Image and Video Processing in Medicine. doi:10.3390/jimaging3010001

95. H. Aliakbarpour, V. B. S. Prasath, K. Palaniappan, G. Seetharaman, J. Dias. Heterogeneous multi-view information fusion: Review of 3-D reconstruction methods and a new registration with uncertainty modeling. IEEE Access, 4(1), 8264-8285, December 2016. doi:10.1109/ACCESS.2016.2629987

96. C. I. Sarmiento, D. San-Juan, V. B. S. Prasath. Brief history of transcranial direct current stimulation (tDCS): From electrical fishes to microcontrollers. Psychological Medicine, 46(15), 3259-3261, November 2016. doi:10.1017/S0033291716001926 

97. V. B. S. Prasath. Adaptive coherence-enhancing diffusion flow for color images. Informatica, 40(3), 337-342, September 2016. doi:Weblink

98. P. Kalavathi, V. B. S. Prasath. Methods on skull stripping of MRI head scan images - A review. Journal of Digital Imaging, 29(3), 365-397, June 2016. doi:10.1007/s10278-015-9847-8

99. J. C. Moreno, V. B. S. Prasath, J. C. Neves. Color image processing by vectorial total variation with gradient channels coupling. Inverse Problems and Imaging, 10(2), 461-497, May 2016. doi:10.3934/ipi.2016008

100. P. Kalavathi, V. B. S. Prasath. Automatic segmentation of cerebral hemispheres in MR human head scans. International Journal of Imaging Systems and Technology - Neuroimaging and Brain Mapping, 26(1), 15-23, April 2016. doi:10.1002/ima.22152

101. J. C. Moreno, V. B. S. Prasath, G. Santos, H. Proenca. Robust periocular recognition by fusing sparse representations of color and geometry information. Journal of Signal Processing Systems, 82(3), 403-417, March 2016. doi:10.1007/s11265-015-1023-3

102. V. B. S. Prasath, D. Vorotnikov, R. Pelapur, S. Jose, G. Seetharaman, K. Palaniappan. Multiscale Tikhonov-total variation image restoration using spatially varying edge coherence exponent. IEEE Transactions on Image Processing, 24(12), 5220-5235, December 2015. doi:10.1109/TIP.2015.2479471

103. H. Aliakbarpour, V. B. S. Prasath, J. Dias. On optimal multi-sensor network configuration for 3D registration. Journal of Sensor and Actuator Networks, 4(4), 293-314, November 2015. Special issue on 3D Wireless Sensor Network. doi:10.3390/jsan4040293

104. V. B. S. Prasath, J. M. Urbano, D. Vorotnikov. Analysis of adaptive forward-backward diffusion flows with applications in image processing. Inverse Problems, 31, 105008 (30pp), October 2015. doi:10.1088/0266-5611/31/10/105008

105. J. C. Moreno, V. B. S. Prasath, H. Proenca, K. Palaniappan. Fast and globally convex multiphase active contours for brain MRI segmentation. Computer Vision and Image Understanding, 125, 237-250, August 2014. doi:10.1016/j.cviu.2014.04.010

106. V. B. S. Prasath, D. Vorotnikov. Weighted and well-balanced anisotropic diffusion scheme for image denoising and restoration. Nonlinear Analysis: Real World Applications, 17, 33-46, June 2014. doi:10.1016/j.nonrwa.2013.10.004

107. V. B. S. Prasath, O. Haddad. Radar shadow detection in synthetic aperture radar images using digital elevation model and projections. Journal of Applied Remote Sensing, 8(1), 083628, May 2014. doi:10.1117/1.JRS.8.083628

108. V. B. S. Prasath, D. Vorotnikov. On a system of adaptive coupled PDEs for image restoration. Journal of Mathematical Imaging and Vision, 48(1), 35-52, January 2014. doi:10.1007/s10851-012-0386-3

109. V. B. S. Prasath, A. Singh. An adaptive anisotropic diffusion scheme for image restoration and selective smoothing. International Journal of Image and Graphics, 12(1), Article ID 1250003, 18 pages, January 2012. doi:10.1142/S0219467812500039

110. V. B. S. Prasath. A well-posed multiscale regularization scheme for digital image denoising. International Journal of Applied Mathematics and Computer Science, 21(4), 769-777, December 2011. doi:10.2478/v10006-011-0061-7

111. P. N. Figueiredo, I. N. Figueiredo, S. Prasath, R. Tsai. Automatic polyp detection in Pillcam Colon 2 Capsule images and videos: Preliminary feasibility report. Diagnostic and Therapeutic Endoscopy, Vol. 2011, Article ID 182435, 7 pages, March 2011. doi:10.1155/2011/182435

112. V. B. S. Prasath, A. Singh. Multichannel image restoration using combined channel information and robust M-estimator approach. International Journal of Tomography and Statistics, 15(10), 9-22, 2010. doi:Weblink

113. V. B. S. Prasath, A. Singh. Well-posed inhomogeneous nonlinear diffusion scheme for digital image denoising. Journal of Applied Mathematics, Vol. 2010, Article ID 763847, 14 pages, April 2010. doi:10.1155/2010/763847

114. V. B. S. Prasath, A. Singh. Multispectral image denoising by well-posed anisotropic diffusion scheme with channel coupling. International Journal of Remote Sensing, 31(8), 2091-2099, March 2010. doi:10.1080/01431160903260965

115. V. B. S. Prasath, A. Singh. A hybrid convex variational model for image restoration. Applied Mathematics and Computation, 215(10), 3655-3664, January 2010. doi:10.1016/j.amc.2009.11.003

Conference Publications:

1. S. Boudissa, S. S. Debsarkar, H. Kawanaka, B. Aronow, V. B. S. Prasath. Vision transformers and CNN-based knowledge-distillation for histopathological image classification. 10th International Conference on Fuzzy Systems and Data Mining (FSDM), Matsue, Japan, November 2024.

2. G. Sumi, B. Iyer, H. Kawanaka, B. J. Aronow, V. B. S. Prasath. Gait analysis for cerebral palsy using memory-augmented auto-encoder model. 11th International Conference on Informatics, Electronics & Vision (ICIEV), London, UK, October 2023. Proc. IEEE. (Excellent Paper Award)

3. G. Sumi, B. Iyer, K. Takumi, H. Kawanaka, B. J. Aronow, V. B. S. Prasath. Gait quality assessment for cerebral palsy using variational auto-encoder. 24th International Symposium on Advanced Intelligent Systems (ISIS), 2023.

4. A. Shukla, N. Lodha, V. Vijayarajan, S. Prasath. Building novel approach for context-based image retrieval in the area of healthcare. First International Conference on Applied Data Science and Smart Systems (ADSSS), India, November 2022. AIP Proceedings. doi:10.1063/5.0180774  (Best Paper Award)

5. A. Shukla, N. Lodha, V. Vijayarajan, S. Prasath. Simulation of content based on image retrieval for financial institutions. First International Conference on Applied Data Science and Smart Systems (ADSSS), India, November 2022. AIP Proceedings. doi:10.1063/5.0180219 

6. S. Bharati, P. Podder, M. R. H. Mondal, V. B. S. Prasath, N. Gandhi. Ensemble learning for data-driven diagnosis of polycystic ovary syndrome. 21st International Conference on Intelligent Systems Design and Applications (ISDA), Seattle, WA USA, December 2021. Proc. Springer LNNS 418, (Eds.: A. Abraham et al.), pp. 1250-1259, March 2022. doi:10.1007/978-3-030-96308-8_116

7. V. B. S. Prasath, N. N. Hien, D. N. H. Thanh, S. Dvoenko. SIMRES-TV: Noise and residual similarity for parameter estimation in total variation. 4th International Workshop on Photogrammetric and Computer Vision Techniques for Video surveillance, Biometrics and Biomedicine (PSBB), Moscow, Russia, April 2021. Proc. ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIV-2/W1, 171-176, April 2021. doi:10.5194/isprs-archives-XLIV-2-W1-2021-171-2021

8. V. B. S. Prasath, D. N. H. Thanh, N. H. Hai, S. Dvoenko. Multiregion multiscale image segmentation with anisotropic diffusion. 7th Workshop Image Mining. Theory and Applications (IMTA VII), January 2021. Proc. Springer LNCS 12665, 129-140, February 2021. doi:10.1007/978-3-030-68821-9_13

9. L. T. Thanh, D. N. H. Thanh, N. N. Hien, U. Erkan, V. B. S. Prasath. Single image dehazing with optimal color channels and nonlinear transformation. International Conference on Communications and Electronics (ICCE), Phu Quoc, Vietnam. Proc. IEEE, 421-426, January 2021. doi:10.1109/ICCE48956.2021.9352087

10. L. T. Thanh, D. N. H. Thanh, N. M. Hue, H. N. T. Linh, V. B. S. Prasath. On numerical implementation of the Laplace equation-based image inpainting. 1st International Conference on Computational Research and Data Analytics (ICCRDA), October 2020. IOP Conference Series: Material Science and Engineering, 1022, 012034, January 2021. doi:10.1088/1757-899X/1022/1/012034

11. D. N. H. Thanh, L. T. Thanh, P. Kalavathi, V. B. S. Prasath. Chest X-ray image denoising using Nesterov optimization method with total variation regularization. 3rd International Conference on Computing and Network Communications (CoCoNet), Trivandrum, India, December 2019. Proc. Elsevier Procedia Computer Science, vol. 171, 1961-1968, May 2020. doi:10.1016/j.procs.2020.04.210

12. D. N. H. Thanh, N. N. Hien, P. Kalavathi, V. B. S. Prasath. Adaptive switching weight mean filter for salt and pepper image denoising. 3rd International Conference on Computing and Network Communications (CoCoNet), Trivandrum, India, December 2019. Proc. Elsevier Procedia Computer Science, vol. 171, 292-301, May 2020. doi:10.1016/j.procs.2020.04.031

13. N. M. Hue, D. N. H. Thanh, L. T. Thanh, N. N. Hien, V. B. S. Prasath. Image denoising with overlapping group sparsity and second order total variation regularization. 6th NAFOSTED Conference on Information and Computer Science (NICS), Hanoi, Vietnam. Proc. IEEE. 370-374, December 2019. doi:10.1109/NICS48868.2019.9023801

14. N. V. Son, D. N. H. Thanh, U. Erkan, V. B. S. Prasath. An image inpainting method based on adaptive fuzzy switching median. 6th NAFOSTED Conference on Information and Computer Science (NICS), Hanoi, Vietnam. Proc. IEEE, 357-362, December 2019. doi:10.1109/NICS48868.2019.9023869

15. S. Isaka, H. Kawanaka, B. Aronow, V. B. S. Prasath. Multi-class segmentation of lung immunofluorescence confocal images using deep learning. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), International Workshop on Deep Learning in Bioinformatics, Biomedicine, and Healthcare Informatics (DLB2H), San Diego, CA, USA. Proc. IEEE, 2362-2368, November 2019. doi:10.1109/BIBM47256.2019.8983146

16. L. T. Thanh, D. N. H. Thanh, V. B. S. Prasath. Adaptive texts deconvolution method for real natural images. 25th Asia-Pacific Conference on Communications (APCC), Ho Chi Minh City, Vietnam. Proc. IEEE, 110-115, November 2019. doi:10.1109/APCC47188.2019.9026515

17. L. T. Thanh, D. N. H. Thanh, N. M. Hue, V. B. S. Prasath. Single image dehazing based on adaptive histogram equalization and linearization of Gamma correction. 25th Asia-Pacific Conference on Communications (APCC), Ho Chi Minh City, Vietnam. Proc. IEEE, 36-40, November 2019. doi:10.1109/APCC47188.2019.9026457

18. N. H. Hai, D. N. H. Thanh, N. N. Hien, C. Premachandra, V. B. S. Prasath. A fast denoising algorithm for X-ray images with variance stabilizing transform. 11th International conference on Knowledge and Systems Engineering (KSE), Da Nang, Vitenam. Proc. IEEE, October 2019. doi:10.1109/KSE.2019.8919364

19. S. M. H. Mousavi, V. B. S. Prasath, S. M. H. Mousavi. Persian classical music instrument recognition (PCMIR) using a novel Persian music database. 9th International Conference on Computer and Knowledge Engineering (ICCKE), Mashhad, Iran. Proc. IEEE, 122-130, October 2019. doi:10.1109/ICCKE48569.2019.8965166. Download dataset at Kaggle: PCMIR-Database

20. D. N. H. Thanh, N. N. Hien, V. B. S. Prasath, U. Erkan, A. Khamparia. Adaptive thresholding skin lesion segmentation with Gabor filters and principal component analysis. 4th International Conference on Research in Intelligent and Computing in Engineering (RICE), Hanoi, Vietnam. Proc. Springer AISC, vol. 1125, 811-820, August 2019. doi:10.1007/978-981-15-2780-7_87

21. A. Al-Btoush, M. A. Abbadi, A. B. Hassanat, A. S. Tarawneh, A. Hasanat, V. B. S. Prasath. New features for eye-tracking systems: Preliminary results. 10th International Conference on Information and Communication Systems (ICICS), Irbid, Jordan. Proc. IEEE, pp. 179-184, June 2019. doi:10.1109/IACS.2019.8809129 

22. D. N. H. Thanh, V. B. S. Prasath, L. M. Hieu, H. Kawanaka. Image inpainting method based on mixed median. Joint 2019 8th International Conference on Informatics, Electronics & Vision (ICIEV) & 3rd International Conference on Imaging, Vision & Pattern Recognition (IVPR), Spokane, WA, USA. Proc. IEEE, pp. 24-29, May 2019. doi:10.1109/ICIEV.2019.8858556

23. D. N. H. Thanh, S. Dvoenko, V. B. S. Prasath, N. H. Hai. Blood vessels segmentation method for retinal fundus images based on adaptive principal curvature and image derivative operators. 3rd International Workshop on Photogrammetric and Computer Vision Techniques for Video surveillance, Biometrics and Biomedicine (PSBB), Moscow, Russia, May 2019. Proc. ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-2/W12, 211-218, May 2019. doi:10.5194/isprs-archives-XLII-2-W12-211-2019

24. D. N. H. Thanh, U. Erkan, V. B. S. Prasath, V. Kumar, N. N. Hien. A skin lesion segmentation method for dermoscopic images based on adaptive thresholding with normalization of color models. 6th International Conference on Electrical and Electronics Engineering (ICEEE), Istanbul, Turkey. Proc. IEEE, pp. 116-120, April 2019. doi:10.1109/ICEEE2019.2019.00030

25. D. N. H. Thanh, Nguyen Van Son, V. B. S. Prasath. Distorted image reconstruction method with trimmed median. 3rd International Conference on Recent Advances in Signal Processing, Telecommunications and Computing (SigTelCom), HaNoi, Vietnam. Proc. IEEE, pp. 58-62, Mar 2019. doi:10.1109/SIGTELCOM.2019.8696138

26. D. N. H. Thanh, L. T. Thanh, V. B. S. Prasath, U. Erkan. An improved BPDF filter for high density salt and pepper denoising. IEEE-RIVF International Conference on Computing and Communication Technologies (RIVF), Danang, Vietnam. Proc. IEEE, Mar 2019. doi:10.1109/RIVF.2019.8713669

27. D. N. H. Thanh, N. N. Hien, V. B. S. Prasath, L. T. Thanh, N. H. Hai. Automatic initial boundary generation methods based on edge detectors for the level set function of the Chan-Vese segmentation model and applications in biomedical image processing. 7th International Conference on Frontiers of Intelligent Computing: Theory and Application (FICTA), Duy Tan University, Da Nang, Vietnam. Proc. Springer AISC 1014 (Eds.: S. C. Satapathy et al.), pp. 171-181, November 2018. doi:10.1007/978-981-13-9920-6_18

28. D. N. H. Thanh, V. B. S. Prasath, L. T. Thanh. Total variation L1 fidelity salt-and-pepper denoising with adaptive regularization parameter. 5th NAFOSTED Conference on Information and Computer Science (NICS), Ho Chi Minh City, Vietnam. Proc. IEEE, pp. 400-405, November 2018. doi:10.1109/NICS.2018.8606870

29. V. B. S. Prasath, D. N. H. Thanh, N. H. Hai. Regularization parameter selection in image restoration with inverse gradient: Single scale or multiscale?. 7th International Conference on Communications and Electronics (ICCE), Hue, Vietnam. Proc. IEEE, pp. 278-282, July 2018. doi:10.1109/CCE.2018.8465720

30. V. B. S. Prasath, D. N. H. Thanh, N. H. Hai. On selecting the appropriate scale in image selective smoothing by nonlinear diffusion. 7th International Conference on Communications and Electronics (ICCE), Hue, Vietnam. Proc. IEEE, pp. 267-272, July 2018. doi:10.1109/CCE.2018.8465764

31. A. Yonekura, H. Kawanaka, V. B. S. Prasath, B. J. Arronow, S. Tsuruoka. Glioma subtypes clustering method using histopathological image analysis. 7th International Conference on Informatics, Electronics and Vision (ICIEV), and 2nd International Conference on Imaging, Vision and Pattern Recognition (icIVPR), Fukuoka, Japan. Proc. IEEE, pp. 442-446, June 2018. doi:10.1109/ICIEV.2018.8641031

32. S. Isaka, H. Kawanaka, V. B. S. Prasath, B. J. Aronow, S. Tsuruoka. Development of a web based image annotation tool for lung immunofluorescent confocal images. 4th International Symposium on Affective Science and Engineering, and the 29th Modern Artificial Intelligence and Cognitive Science Conference (ISASE-MAICS), Spokane, WA, USA, June 2018. doi:10.5057/isase.2018-C000036

33. V. B. S. Prasath, D. N. H. Thanh, N. H. Hai, N. X. Cuong. Image restoration with total variation and iterative regularization parameter estimation. International Symposium on Information and Communication Technology (SoICT), Nha Trang, Vietnam. Proc. ACM, pp. 378-384, December 2017. doi:10.1145/3155133.3155191

34. V. B. S. Prasath, H. Kawanaka. Near-light perspective shape from shading for 3D visualizations in endoscopy systems. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Kansas, MO, USA. Proc. IEEE, pp. 2293-2295, November 2017. doi:10.1109/BIBM.2017.8218031. Available at figshare: doi:10.6084/m9.figshare.5526907 

35. A. Yonekura, H. Kawanaka, V. B. S. Prasath, B. J. Aronow, H. Takase. Improving the generalization of disease stage classification with deep CNN for glioma histopathological images. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), International Workshop on Deep Learning in Bioinformatics, Biomedicine, and Healthcare Informatics (DLB2H), Kansas, MO, USA. Proc. IEEE, pp. 1222-1226, November 2017. doi:10.1109/BIBM.2017.8217831

36. R. Pelapur, V. B. S. Prasath, J. C. Moreno, M. Heck. 3D Workflow for segmentation and interactive visualization in brain MR images using multiphase active contours. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Kansas, MO, USA. Proc. IEEE, pp. 921-926, November 2017. doi:10.1109/BIBM.2017.8217780

37. Y. M. Kassim, V. B. S. Prasath, O. V. Glinskii, V. V. Glinsky, V. H. Huxley, K. Palaniappan. Microvasculature segmentation of arterioles using deep CNN. IEEE International Conference on Image Processing (ICIP), Beijing, China. Proc. IEEE, pp. 580-584, September 2017. doi:10.1109/ICIP.2017.8296347. Slides available at Sigport.

38. A. Yonekura, H. Kawanaka, V. B. S. Prasath, B. J. Aronow, H. Takase. Glioblastoma Multiforme tissue histopathology images based disease stage classification with deep CNN. 6th International Conference on Informatics, Electronics & Vision (ICIEV), Himeji, Hyogo, Japan. Proc. IEEE, September 2017. doi:10.1109/ICIEV.2017.8338558 (Best Paper Award Finalist)

39. A. Hassanat, E. Btoush, M. Ali Abbadi, B. M. Al-Mahadeen, M. Al-Awadi, K. I. A. Mseidein, A. M. Almseden, A. S. Tarawneh, M. B. Alhasanat, V. B. S. Prasath, F. A. Al-Alem. Victory sign biometric for terrorists identification: Preliminary results. International Conference on Information and Communication Systems (ICICS), Irbid, Jordan. Proc. IEEE, pp. 182-187, April 2017. doi:10.1109/IACS.2017.7921968 (MIT Technology Review)

40. V. B. S. Prasath, Y. M. Kassim, Z. A. Oraibi, J.-B. Guiriec, A. Hafiane, K. Palaniappan. HEp-2 cell classification and segmentation using motif texture patterns and spatial features with random forests. 23rd International Conference on Pattern Recognition, International Contest on Pattern Recognition Techniques for Indirect Immunofluorescence Images Analysis, Cancun, Mexico. Proc. IEEE, pp. 90-95, December 2016. doi:10.1109/ICPR.2016.7899614

41. R. Aktar, V. B. S. Prasath, H. Aliakbarpour, U. Sampathkumar, G. Seetharaman, K. Palaniappan. Video haze removal and Poisson blending based mini-mosaics for wide area motion imagery. IEEE Applied Imagery Pattern Recognition (AIPR), Washington DC, October 2016. Proc. IEEE. doi:10.1109/AIPR.2016.8010552. Available at figshare: doi:10.6084/m9.figshare.4028409.v1

42. U. Sampathkumar, V. B. S. Prasath, S. Meena, K. Palaniappan. Assisted ground truth generation using interactive segmentation on a visualization and annotation tool. IEEE Applied Imagery Pattern Recognition (AIPR), Washington DC, October 2016. Proc. IEEE. doi:10.1109/AIPR.2016.8010603. Available at figshare: doi:10.6084/m9.figshare.4036245

43. V. B. S. Prasath, S. Surineni, K. Gao, G. Seetharaman, K. Palaniappan. CSANG: Continuous scale anisotropic Gaussians for robust linear structure extraction. IEEE Applied Imagery Pattern Recognition (AIPR), Washington DC, October 2016. Proc. IEEE. doi:10.1109/AIPR.2016.8010551. Available at figshare: doi:10.6084/m9.figshare.3175450

44. Y. M. Kassim, V. B. S. Prasath, O. Glinskii, V. Glinsky, V. Huxley, K. Palaniappan. Confocal vessel structure segmentation with optimized feature bank and random forests. IEEE Applied Imagery Pattern Recognition (AIPR), Washington DC, October 2016. Proc. IEEE. doi:10.1109/AIPR.2016.8010580

45. K. Fukuma, V. B. S. Prasath, H. Kawanaka, B. J. Aronow, H. Takase. A study on nuclei segmentation, feature extraction and disease stage classification for human brain histopathological images. 20th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES), York, UK. Procedia Computer Science, 96, pp. 1202-1020, September 2016. doi:10.1016/j.procs.2016.08.164

46. S. Meena, V. B. S. Prasath, Y. M. Kassim, R. J. Maude, O. V. Glinskii, V. V. Glinsky, V. Huxley, K. Palaniappan. Multiquadric spline-based interactive segmentation of vascular networks. 38th Annual International Conference of the Engineering in Medicine and Biology Society (IEEE EMBC), Orlando, FL, USA. Proc. IEEE, pp. 5913-5916, August 2016. doi:10.1109/EMBC.2016.7592074

47. Y. M. Kassim, V. B. S. Prasath, R. Pelapur, O. Glinskii, R. J. Maude, V. Glinsky, V. Huxley, K. Palaniappan. Random forests for dura mater microvasculature segmentation using epifluorescence images. 38th Annual International Conference of the Engineering in Medicine and Biology Society (IEEE EMBC), Orlando, FL, USA. Proc. IEEE, pp. 2901-2904, August 2016. doi:10.1109/EMBC.2016.7591336 (EMBS Student Paper Competition Finalist) 

48. K. Fukuma, V. B. S. Prasath, H. Kawanaka, B. J. Aronow, H. Takase. A study on feature extraction and disease stage classification for glioma pathology images. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Vancouver, Canada. Proc. IEEE, pp. 2150-2156, July 2016. doi:10.1109/FUZZ-IEEE.2016.7737958

49. V. B. S. Prasath, P. Kalavathi. Mixed noise removal using hybrid fourth order mean curvature motion. 2nd International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS), Trivandrum, India. Proc. Springer Advances in Intelligent Systems and Computing 425 (Eds.: S. M. Thampi, S. Bandyopadhyay, S. Krishnan, K.-C. Li, S. Mosin and M. Ma), pp. 625-632, December 2015. doi:10.1007/978-3-319-28658-7_53

50. V. B. S. Prasath, P. Kalavathi. Adaptive nonlocal filtering for brain MRI restoration. 2nd International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS), Trivandrum, India. Proc. Springer Advances in Intelligent Systems and Computing 425 (Eds.: S. M. Thampi, S. Bandyopadhyay, S. Krishnan, K.-C. Li, S. Mosin and M. Ma), pp. 571-580, December 2015. doi:10.1007/978-3-319-28658-7_48

51. V. B. S. Prasath, R. Delhibabu. Automatic mucosa detection in video capsule endoscopy with adaptive thresholding. International Conference on Computational Intelligence in Data Mining (ICCIDM), Odisha, India. Proc. Springer SIST 410 (Eds.: H. S. Behera, D. P. Mohapatra), pp. 95-102, December 2015. doi:10.1007/978-81-322-2734-2_10

52. V. B. S. Prasath, H. Kawanaka. Vascularization features for polyp localization in capsule endoscopy. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Washington, DC, USA. Proc. IEEE, pp. 1740-1742, November 2015. doi:10.1109/BIBM.2015.7359946. Available at figshare: doi:10.6084/m9.figshare.1585847 

53. V. B. S. Prasath, K. Fukuma, B. J. Aronow, H. Kawanaka. Cell nuclei segmentation in glioma histopathology images with color decomposition based active contours. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Washington, DC, USA. Proc. IEEE, pp. 1734-1736, November 2015. doi:10.1109/BIBM.2015.7359944. Available at figshare: doi:10.6084/m9.figshare.1588805

54. K. Fukuma, H. Kawanaka, S. Prasath, B. J. Aronow, H. Takase. Feature extraction and disease stage classification for glioma histopathology images. IEEE 17th International Conference on E-Health Networking, Applications & Services (Healthcom), Boston, USA. Proc. IEEE, pp. 598-599, October 2015. doi:10.1109/HealthCom.2015.7454574

55. V. B. S. Prasath. On fuzzification of color Spaces for medical decision support in wireless capsule endoscopy. Modern Artificial Intelligence and Cognitive Science Conference (MAICS), Greensboro, NC, USA. Proc. IEUR (Eds. M. Glass J. H. Kim), pp. 147-151, April 2015. http://ceur-ws.org/Vol-1353/paper_20.pdf 

56. V. B. S. Prasath, R. Pelapur, O. Glinskii, V. Glinsky, V. Huxley, K. Palaniappan. Multiscale tensor anisotropic filtering of fluorescence microscopy for denoising microvasculature. IEEE International Symposium on Biomedical Imaging (ISBI), New York, USA. Proc. IEEE, pp. 540-543, April 2015. doi:10.1109/ISBI.2015.7163930 Available at figshare: doi:10.6084/m9.figshare.1309773

57. V. B. S. Prasath, R. Delhibabu. Color image restoration with fuzzy Gaussian mixture model driven nonlocal filter. 4th Analysis of Images, Social Networks, and Texts (AIST), Yekaterinburg, Russia. Proc. in Springer CCIS 542 (Eds.: M. Khachay, N. Konstantinova, A. Panchenko, D. I. Ignatov, G. V. Labunets), pp. 131-139, April 2015. doi:10.1007/978-3-319-26123-2_13 

58. V. B. S. Prasath, R. Delhibabu. Automatic image segmentation for video capsule endoscopy. International Conference on Computational Intelligence: Health and Disease (CIHD), Visakhapatnam, India, Dec 2014. Computational Intelligence in Medical Informatics. Springer Briefs in Forensic and Medical Bioinformatics (Eds. N. B. Muppalaneni, V. K. Gunjan), pp. 73-80, 2015. doi:10.1007/978-981-287-260-9_7

59. V. B. S. Prasath, R. Delhibabu. Automatic contrast enhancement for wireless capsule endoscopy videos with spectral optimal contrast-tone mapping. International Conference on Computational Intelligence in Data Mining (ICCIDM), Odisha, India, December 2014. Proc. Springer SIST (Eds.: L. Jain, H. S. Behera, J. K. Mandal, D. P. Mohapatra), pp. 243-250, 2015. doi:10.1007/978-81-322-2205-7_23

60. V. B. S. Prasath, R. Delhibabu. Image inpainting with modified F-transform. 5th Joint International Conference on Swarm, Evolutionary and Memetic Computing (SEMCCO) & Fuzzy and Neural Computing (FANCCO), Odisha, India, December 2014. Proc. Springer LNCS 8947, pp. 856-867. (Eds.: B. K. Panigrahi, P. N. Suganthan, S. Das), August 2015. doi:10.1007/978-3-319-20294-5_73

61. V. B. S. Prasath, R. Delhibabu. Image restoration with fuzzy coefficient driven anisotropic diffusion. 5th Joint International Conference on Swarm, Evolutionary and Memetic Computing (SEMCCO) & Fuzzy and Neural Computing (FANCCO), Odisha, India, December 2014. Proc. in Springer LNCS 8947, pp. 145-155. (Eds.: B. K. Panigrahi, P. N. Suganthan, S. Das), August 2015. doi:10.1007/978-3-319-20294-5_13

62. S. Meena, V. B. S. Prasath, K. Palaniappan, G. Seetharaman. Elastic body spline based image segmentation. IEEE International Conference on Image Processing (ICIP), Paris, France, October 2014. Proc. IEEE, pp. 4378-4382. doi:10.1109/ICIP.2014.7025888. Available at figshare: doi:10.6084/m9.figshare.1203638

63. R. Pelapur, V. B. S. Prasath, F. Bunyak, O. Glinskii, V. Glinsky, V. Huxley, K. Palaniappan. Multi-focus image fusion using epifluorescence microscopy for robust vascular segmentation. 36th Annual International Conference of the Engineering in Medicine and Biology Society (IEEE EMBC), Chicago, IL, USA. Proc. IEEE, pp. 4735-4738, August 2014. doi:10.1109/EMBC.2014.6944682 Available at figshare: doi:10.6084/m9.figshare.1147490

64. V. B. S. Prasath, S. Pelapur, K. Palaniappan, G. Seetharaman. Feature fusion and label propagation for textured object video segmentation. Geospatial Info-Fusion and Video Analytics IV, SPIE Defense+Security (DSS), Baltimore Convention Center, Baltimore, Maryland, USA, May 2014. Proc. SPIE. Vol. 9089. doi:10.1117/12.2052983

65. V. B. S. Prasath, R. Delhibabu. Automatic contrast parameter estimation in anisotropic diffusion for image restoration. Analysis of Images, Social Networks, and Texts (AIST), Yekaterinburg, Russia. Proc. in Springer Communications in Computer and Information Science 436 (Eds.: D. I. Ignatov, M. Khachay, A. Panchenko, N. Konstantinova, R. Yavorsky), pp. 198-206, April 2014. doi:10.1007/978-3-319-12580-0_20 (Best Paper Award)

66. V. B. S. Prasath, J. C. Moreno. Feature preserving anisotropic diffusion for image restoration. 4th National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), IIT Jodhpur, India. Proc. IEEE, pp. 1-4, December 2013. doi:10.1109/NCVPRIPG.2013.6776250

67. J. C. Moreno, V. B. S. Prasath, H. Proenca. Robust periocular recognition by fusing local to holistic sparse representations. 6th International Conference on Security of Information and Networks (SIN), Aksaray, Turkey. Proc. ACM Digital Library. pp. 160-164, November, 2013. doi:10.1145/2523514.2523540

68. V. B. S. Prasath, O. Haddad, F. Bunyak, O. Glinskii, V. Glinsky, V. Huxley, K. Palaniappan. Robust filtering based segmentation of Dura Mater Laminae using fluorescence microscopy. 35th Annual International Conference of the Engineering in Medicine and Biology Society (IEEE EMBC), Osaka, Japan. Proc. IEEE, pp. 6055-6058, July 2013. doi:10.1109/EMBC.2013.6610933

69. V. B. S. Prasath, K. Palaniappan, G. Seetharaman. Multichannel texture image segmentation using local feature fitting based variational active contours. 8thIndian Conference on Vision, Graphics and Image Processing (ICVGIP), IIT Bombay, Mumbai, India, December, 2012. Proc. ACM Digital Library. doi:10.1145/2425333.2425411

70. V. B. S. Prasath, F. Bunyak, P. Dale, S. R. Frazier, K. Palaniappan. Segmentation of breast cancer tissue microarrays for computer-aided diagnosis in pathology. First IEEE Healthcare Technology Conference: Translational Engineering in Health & Medicine, Houston, TX, USA. Proc. in IEEE, pp. 40-43, November, 2012. doi:Weblink

71. I. N. Figueiredo, J. C. Moreno, V. B. S. Prasath. Texture image segmentation with smooth gradients and local information. Computational Modeling of Objects Presented in Images: Fundamentals, Methods and Applications (CompIMAGE), Rome, Italy. Proc. CRC Press (Eds.: P. D. Giamberardino, D. Iacoviello, J. M. R. S. Tavares, R. M. N. Jorge), pp. 115-119, September, 2012. doi:10.1201/b12753-28

72. V. B. S. Prasath, I. N. Figueiredo, P. N. Figueiredo, K. Palaniappan. Mucosal region detection and 3D reconstruction in wireless capsule endoscopy videos using active contours. 34th Annual International Conference of the Engineering in Medicine and Biology Society (IEEE EMBC), San Diego, USA. Proc. IEEE, pp. 4014-4017, August 2012. doi:10.1109/EMBC.2012.6346847

73. I. N. Figueiredo, J. C. Moreno, V. B. S. Prasath, P. N. Figueiredo. A segmentation model and application to endoscopic images. International Conference on Image Analysis and Recognition (ICIAR), Aveiro, Portugal. Proc. in Springer LNCS 7325 (Eds.: A. Campilho and M. Kamel), Part II, pp. 164-171, June 2012. doi:10.1007/978-3-642-31298-4_20

74. V. B. S. Prasath. Weighted Laplacian differences based multispectral anisotropic diffusion. IEEE Geoscience and Remote Sensing Symposium (IGARSS), Vancouver, BC, Canada. Proc. in IEEE, pp. 4042-4045, July 2011. doi:10.1109/IGARSS.2011.6050119

75. V. B. S. Prasath. Color image segmentation based on vectorial multiscale diffusion with inter-scale linking. 3rd International Conference on Pattern Recognition and Machine Intelligence (PReMI), Delhi, India. Proc. in Springer LNCS 5909. (Eds.: S. Chaudhury, S. Mitra, C. A. Murthy, P. S. Sastry, Sankar K. Pal), pp. 339-344, December 2009. doi:10.1007/978-3-642-11164-8_55

76. V. B. S. Prasath, A. Singh. Ringing artifact reduction in blind image deblurring and denoising problems by regularization methods. 7th International Conference on Advances in Pattern Recognition (ICAPR), Kolkata, India. Proc. in IEEE Computer Society, pp. 333-336, February 2009. doi:10.1109/ICAPR.2009.57

77. V. B. S. Prasath, A. Singh. Edge detectors based anisotropic diffusion for enhancement of digital images. 6th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), Bhubaneswar, India. Proc. in IEEE Computer Society, pp. 33-38, December 2008. (Best Paper Award) doi:10.1109/ICVGIP.2008.68

78. V. B. S. Prasath, A. Singh. Controlled inverse diffusion models for image restoration and enhancement. First International Conference on Emerging Trends in Engineering and Technology (ICETET), Nagpur, India. Proc. in IEEE Computer Society, pp. 90-94, July 2008. doi:10.1109/ICETET.2008.69 

Preprints: arXiv, bioRχiv, medRχiv, TechRxiv

1. J. Reigle, O. Lopez-Nunez, E. Drysdale, D. Abuquteish, X. Liu, J. Putra, L. Erdman, A. M. Griffiths, S. Prasath, I. Siddiqui, J. Dhaliwal. Using deep learning to automate eosinophil counting in pediatric ulcerative colitis histopathological images. medRxiv, April 2024. 10.1101/2024.04.03.24305251

2. S. Rawat, V. Vijayarajan, V. B. S. Prasath. Modified K-means with cluster assignment - Application to COVID-19 data. arXiv, February 2024. doi:10.48550/arXiv.2402.03380

3. X. Liu, T. Walters, I. Siddiqui, O. Lopez-Nunez, S. Prasath, L. A Denson, PROTECT consortium, J. Dhaliwal. Machine learning-based prediction of pediatric ulcerative colitis treatment response using diagnostic histopathology. medRxiv, January 2024. doi:10.1101/2024.01.22.24301559

4. El Hadji S. Diop, Valerie Burdin, V. B. S. Prasath. Note on the existence of minimizers for variational geometric active contours. arXiv, October 2022. doi:10.48550/arXiv.2210.12773.

5. S. Bharati, M. R. H. Mondal, P. Podder, V. B. S. Prasath. Federated learning: Applications, challenges and future scopes. arXiv, May 2022. doi:10.48550/arXiv.2205.09513 

6. S. Bharati, M. R. H. Mondal, P. Podder, V. B. S. Prasath. Deep learning for medical image registration: A comprehensive review. arXiv, April 2022. doi:10.48550/arXiv.2204.11341 

7. K. Jin, D. Schnell, G. Li, N. Salomonis, S. Prasath, R. Szczesniak, B. J. Aronow. CellDrift: Inferring perturbation responses in temporally-sampled single cell data. Biorxiv, April 2022. doi:10.1101/2022.04.13.488194

8. T. A Cazares, F. W. Rizvi, B. Iyer, X. Chen, M. Kotliar, J. A. Wayman, A. Bejjani, O. Donmez, B. Wronowski, S. Parameswaran, L. C. Kottyan, A. Barski, M. T. Weirauch, V. B. S. Prasath, E. R. Miraldi. maxATAC: genome-scale transcription-factor binding prediction from ATAC-seq with deep neural networks. Biorxiv, January 2022. doi:10.1101/2022.01.28.478235

9. N. Gaddis, J. Fortriede, M. Guo, E. E. Bardes, M. Kouril, S. Tabar, K. Burns, M. E. Ardini-Poleske, S. Loos, D. Schnell, K. Jin, B. Iyer, Y. Du, B.-X. Huo, A. Bhattacharjee, J. Korte, R. Munshi, V. Smith, A. Herbst, J. A. Kitzmiller, G. C. Clair, J. Carson, J. Adkins, E. E. Morrisey, G. S. Pryhuber, R. Misra, J. A. Whitsett, X. Sun, T. Heathorn, B. Paten, V. B. S. Prasath, Y. Xu, T. Tickle, B. J. Aronow, N. Salomonis. LungMAP portal ecosystem: Systems-level exploration of the lung. Biorxiv, December 2021. doi:10.1101/2021.12.05.471312

10. A. B. Hassanat, A. Albustanji, A. S. Tarawneh, M. Alrashidi, H. Alharbi, M. Alanazi, M. Alghamdi, I. S. Alkhazi, V. B. S. Prasath. Deep learning for identification and face, gender, expression recognition under constraints. arXiv, November 2021. doi:10.48550/arXiv.2111.01930

11. G. Li, B. Song, H. L. Grimes, V. B. S. Prasath, N. Salomonis. scTriangulate: Decision-level integration of multimodal single-cell data. Biorxiv, October 2021. doi:10.1101/2021.10.16.464640

12.  S. Bharati, P. Podder, M. R. H. Mondal, V. B. S. Prasath. Medical imaging with deep learning for COVID-19 diagnosis: A comprehensive review. arXiv, July 2021. doi:10.48550/arXiv.2107.09602

13. G. Li, B. Iyer, V. B. S. Prasath, Y. Ni, N. Salomonis. DeepImmuno: Deep learning-empowered prediction and generation of immunogenic peptides for T cell immunity. Biorxiv, December 2020. doi:10.1101/2020.12.24.424262

14. V. B. S. Prasath, H. A. A. Alfeilat, A. B. A. Hassanat, O. Lasassmeh, A. S. Tarawneh, M. B. Alhasanat, H. S. E. Salman. Distance and similarity measures effect on the performance of k-nearest neighbor classifier - A review. arXiv, August 2018. doi:10.48550/arXiv.1708.04321 

15. H. T. Amaral-Silva, L. O. Murta-Jr, P. M. Azevedo-Marques, L. Wichert-Ana, V. B. S. Prasath, C. Studholme. Validation of Tsallis entropy in inter-modality neuroimage registration. arXiv, November 2016. doi:10.48550/arXiv.1611.01730 

16. V. B. S. Prasath. Polyp detection and segmentation from video capsule endoscopy: A review. arXiv, September 2016. doi:10.48550/arXiv.1609.01915 

17. V. B. S. Prasath, D. Vorotnikov. On time adaptive critical variable exponent vectorial diffusion flows and their applications in image processing. arXiv, March 2016. doi:10.48550/arXiv.1603.06337 

18. J. C. Moreno, V. B. S. Prasath, D. Vorotnikov. Adaptive diffusion constrained total variation scheme with application to ‘cartoon + texture + edge’ image decomposition. Preprint 13-54, Department of Mathematics, University of Coimbra, Portugal, December 2013. arXiv, May 2015. doi:10.48550/arXiv.1505.00866 

19. V. B. S. Prasath, J. C. Moreno. On convergent finite difference schemes for variational - PDE based image processing. arXiv, October 2013. doi:10.48550/arXiv.1310.7443 

20. J. C. Moreno, V. B. S. Prasath, G. Santos, H. Proenca. Robust periocular recognition by fusing sparse representations of color and geometry information. arXiv, September 2013. doi:10.48550/arXiv.1309.2752 

21. V. B. S. Prasath, O. Haddad. Radar shadow detection in SAR images using DEM and projections. arXiv, September 2013. doi:10.48550/arXiv.1309.1830

22. J. C. Moreno, V. B. S. Prasath, H. Proenca, K. Palaniappan. Brain MRI segmentation with fast and globally convex multiphase active contours. arXiv, August 2013. doi:10.48550/arXiv.1308.6056

23. V. B. S. Prasath, J. C. Moreno. Color image denoising by chromatic edges based vector valued diffusion. arXiv, April 2013. doi:10.48550/arXiv.1304.5587 Supplementary files, data set containing images, results are available at figshare: doi:10.6084/m9.figshare.658958

24. V. B. S. Prasath, D. Vorotnikov. On a coupled PDE model for image restoration. arXiv, December 2011. doi:10.48550/arXiv.1112.2904

25. I. N. Figueiredo, J. C. Moreno, S. Prasath, P. N. Figueiredo. A segmentation model using image gradient information and applications to endoscopic images. September 2010. Preprint 10-30, Department of Mathematics, University of Coimbra, Portugal.

26. I. N. Figueiredo, S. Prasath, Y.-H. R. Tsai, P. N. Figueiredo. Automatic detection and segmentation of colonic polyps in wireless capsule images. UCLA CAM Report 10-65, September 2010. Also available as Preprint 10-37, Department of Mathematics, University of Coimbra, Portugal.

Abstracts/Posters/Presentations: Trainee's underlined -  Please see Student Success (after 2018)

1. Leonardo Ferreira, Robert Hopkin, S. Prasath. ChatGENE: Early Results. Human and Mammalian Genetics and Genomics: The 65th McKusick Short Course, The Jackson Laboratory, Bar Harbor ME, USA, July 2024. Poster presentation.

2. Satoshi Shirae, Shyam Debsarkar, H. Kawanaka, B. Aronow, V. B. S. Prasath. Multimodal and multichannel ensemble deep learning using histopathology and clinical data for brain glioma classification. 3rd Annual Cincy Neuroscience Retreat, May 2024. Poster presentation.

3. Pankaj Rajdeo, B. Aronow, V. B. S. Prasath. Breaking new ground in biomedical AI: Harnessing data to boost LLM capabilities with a superior hybrid RAG pipeline. Second Annual Cincinnati Children's Research Symposium, May 2024. Poster presentation. 

4. Shyam Debsarkar, B. Aronow, V. B. S. Prasath. Enhancing deep learning frameworks for improved nuclei detection across multiple histological datasets. Second Annual Cincinnati Children's Research Symposium, May 2024. Poster presentation.

5. Akshata N. Rudrapatna, X. Chen, P. Nguyen, A. Bejjani, J. Calis, E. Iverson, R. S. Patel, O. Danziger, P. Cohen, F. Gorgy, E. A. Barrall, E. DeGrace, S. Uhl, A. Kuo, P. Falci, A. Pankow, J. A. Wayman, M. A. Scull, B. R. Rosenberg, V. B. S. Prasath, L. C. Kottyan, M. T. Weirauch, E. R. Miraldi. Application of maxATAC transcription factor binding predictions to gene regulatory network inference from scRNA-seq and scATAC-seq. The fifteenth Cold Spring Harbor conference on Systems Biology: Global Regulation of Gene Expression, March 2024.

6. Xiaoxuan Liu, O. Lopez-Nunez, M. H. Collins, L. A. Denson, PROTECT consortium, S. Prasath, A. G. Jegga, J. Dhaliwal. Functional characterization of histomic features identified by machine learning of histopathology images from pediatric patients with ulcerative colitis. Digestive Health Center (DHC) Annual Scientific Symposium, Cincinnati, OH, USA, February 2024.

7. V. B. S. Prasath. More wiggle room - AI-based reconstruction of mucosal surfaces for 3D endoscopy visualization. IBD Horizons, Cincinnati, USA, February 2024. 

8. V. B. S. Prasath. Artificial Intelligence in Capsule Endoscopy: Are we on the cusp?. IBD Horizons, Cincinnati, USA, February 2024.

9. Balaji Iyer, B. Aronow, V. B. S. Prasath. AI-driven gait parameters estimation from videos for cerebral palsy patients. Advancing Healthcare Innovation Summit (AHIS), November 2023. (2nd Best Presentation Award)

10. Shyam Debsarkar, Riku Nakagaki, H. Kawanaka, B. Aronow, V. B. S. Prasath. Multimodal deep learning based IDH1 mutation prediction using histopathology and clinical data. Advancing Healthcare Innovation Summit (AHIS), November 2023.

11. Balaji Iyer, Smruti Deoghare, Krish Ranjan, B. Aronow, V. B. S. Prasath. Deep learning-based segmentation of human epithelial type-2 (HEp-2) cells using indirect immunofluorescence (IIF) images. Advancing Healthcare Innovation Summit (AHIS), November 2023.

12. Smruti Deoghare, Phuc Ngoc Thien Ngyuen, A. T. Trout, J. R. Dillman, V. B. S. Prasath. Deepfaking medical images: Generating high-fidelity pediatric liver ultrasound images with artificial intelligence (AI). First Annual Cincinnati Children's Research Symposium, November 2023. Poster presentation. 

13. Balaji Iyer, B. Aronow, V. B. S. Prasath. ConIFSeg - Confocal immunofluorescence image segmentation with deep learning for discerning developing lung structures. First Annual Cincinnati Children's Research Symposium, November 2023. Poster presentation. 

14. Balaji Iyer, Smruti Deoghare, Krish Ranjan, B. Aronow, V. B. S. Prasath. Deep learning based segmentation of human epithelial type-2 (HEp-2) cells using indirect immunofluorescence (IIF) images. First Annual Cincinnati Children's Research Symposium, November 2023. Poster presentation. 

15. Satoshi Shirae, Shyam Debsarkar, H. Kawanaka, B. Aronow, V. B. S. Prasath. Multimodal and multichannel ensemble deep learning using histopathology and clinical data for brain glioma classification. International Graduate Research Symposium, University of Cincinnati, USA, November 2023. Poster presentation.

16. Satoshi Shirae, Shyam Debsarkar, H. Kawanaka, B. Aronow, V. B. S. Prasath. Multimodal and multichannel ensemble deep learning using histopathology and clinical data for brain glioma classification. Biomedical Informatics (BMI) & Cancer and Blood Diseases Institute (CBDI) Retreat, CCHMC, October 2023. Poster presentation.

17. Ginga Sumi, Balaji Iyer, Hiroharu Kawanaka, Bruce Aronow, V. B. S. Prasath. Gait analysis for cerebral palsy using memory-augmented auto-encoder model. 11th International Conference on Informatics, Electronics & Vision (ICIEV), London, UK, October 2023. Proc. IEEE. (Excellent Paper Award)

18. Xiaoxuan Liu, J. Reigle, S. Prasath, J. Dhaliwal. Assessment of risk of bias in artificial intelligence-based imaging models in inflammatory bowel disease - a systematic review. Digestive Disease Week (DDW), San Diego, CA USA, May 2023.

19. Nicholas Denson, J. Dexheimer, J. Smith, R. Murphy, V. Sharma, Xiaoxuan Liu, S. Prasath, Y. Ni, James Reigle, J. Dhaliwal. Entity and relation identification in unstructured endoscopy reports. Digestive Disease Week (DDW), San Diego, CA USA, May 2023. Poster presentation. (Poster of Distinction)

20. Riku Nakagaki, Shyam Debsarkar, Hiroharu Kawanaka, Bruce Aronow, V. B. S. Prasath.  Multimodal deep learning based IDH1 mutation prediction using histopathology and clinical data.  2nd Annual Cincy Neuroscience Retreat, May 2023. 

21. Balaji Iyer, Aimee Miley, Kelly Greve, Jason Long, Amy Bailes, Sydney Thompson, Mary McMahon, Jilda Vargus-Adams, Alexis Mitelpunkt, Brad Kurowski, Bruce Aronow, V. B. S. Prasath. AI-driven gait parameters estimation from videos for cerebral palsy patients. First Annual Cincinnati Children's Research Symposium, May 2023.

22. Smruti Deoghare, Neelakshi Chatterjee, Shyam Debsarkar, Aniruddha Shekara, Balaji Iyer, A. Schapiro, K. Dufendach, M. Shah, V. B. S. Prasath. PICCLineNet: Detecting peripherally inserted central catheter (PICC) lines and tip malpositioning in neonate X-ray images using artificial intelligence (AI) models. First Annual Cincinnati Children's Research Symposium, May 2023.

23. Smruti Deoghare, Phuc Ngoc Thien Ngyuen, A. T. Trout, J. R. Dillman, V. B. S. Prasath. Fake it till you make it: Generative AI models for creating realistic artificial pediatric liver ultrasound images. Ultracon, Orlando, FL, USA, March 2023.

24. V. B. S. Prasath. Artificial Intelligence in Capsule Endoscopy: Are we on the cusp?. IBD Horizons, Cincinnati, USA, 11 February 2023. (2nd Best Abstract Award)

25. J. Dhaliwal, Xiaoxuan Liu, James Reigle, M. Sharma, O. Lopez-Nunez, T. Walters, M. Collins, J. Hyams, I. Siddiqui, L. Denson, A. Jegga, S. Prasath. Development of an optimal machine learning model using treatment naive diagnostic pathology images to predict steroid-free clinical remission at one year in pediatric ulcerative colitis. Crohn's & Colitis Congress, January 2023, Denver, CO, USA. Poster presentation. Inflammatory Bowel Diseases, Volume 29, Issue Supplement 1, Pages S56-S57, February 2023. doi:10.1093/ibd/izac247.109 

26. Xiaoxuan Liu, James Reigle, O. Nunez-Lopez, I. Siddiqui, T. D. Walters, J. S. Hyams, L. A. Denson, S. Prasath, J. Dhaliwal. Machine learning using standard of care pathology images predicts corticosteroid free remission at one year in pediatric ulcerative colitis. NASPGHAN/CPNP/APGNN Annual Meeting, Orlando, FL, USA, October 2022. Poster presentation.

27. Kang Jin, Daniel Schnell, Guangyuan Li, Nathan Salomonis, V. B. S. Prasath, Rhonda Szczesniak, Bruce Aronow. CellDrift: Inferring perturbation responses in temporally-sampled single cell data. Computational Modeling of Biological Systems (SysMod) Community of Special Interest (COSI), Intelligent Systems for Molecular Biology (ISMB), Madison, WI, USA, July 2022. Poster presentation. (2nd Best Poster Award)

28. Tareian Cazares, Faiz Rizvi, Balaji Iyer, Xiaoting Chen, Michael Kotliar, Joseph Wayman, Anthony Bejjani, Omer Donmez, Benjamin Wronowski, Sreeja Parameswaran, Leah Kottyan, Artem Barski, Matthew Weirauch, V. B. S. Prasath, Emily Miraldi. maxATAC: Predicting transcription factor binding at disease risk loci from ATAC-seq and DNA sequence with convolutional neural networks. Machine Learning in Computational and Systems Biology (MLCSB)  Community of Special Interest (COSI), Intelligent Systems for Molecular Biology (ISMB), Madison, WI, USA, July 2022. Poster presentation.

29. Xiaoxuan Liu, James Reigle, Erik Drysdale, Oscar Nunez-Lopez, Iram Siddiqui, Thomas D. Walters, Jeffrey S. Hyams, Lee A. Denson, S. Prasath, Jasbir Dhaliwal. One year corticosteroid free remission in pediatric Ulcerative Colitis predicted by machine learning models for histopathological classification. Digestive Disease Week (DDW), San Diego, CA, USA, May 2022. Poster presentation. doi:10.1016/S0016-5085(22)61510-5

30. Jasbir Dhaliwal, Erik Drysdale, Oscar Nunez-Lopez, Xiaoxuan Liu, James Reigle, Dua Abuquteish, Juan Putra, Jeffrey S. Hyams, S. Prasath, Anna Goldenberg, Thomas D. Walters, Lee A. Denson, Iram Siddiqui. Employing deep learning approaches to automate eosinophilic cell counting in pediatric UC. Digestive Disease Week (DDW), San Diego, CA, USA, May 2022. Poster presentation. doi:10.1016/S0016-5085(22)61512-9

31. Phuc Ngoc Thien Ngyuen, Smruti Deoghare, Andrew T. Trout, Jonathan R. Dillman, Vasundhara Acharya, V. B. S. Prasath. Fake it till you make it: Synthetic generation of pediatric liver ultrasound images using generative AI models. Undergraduate Research Showcase, University of Cincinnati, April 2022. Poster presentation. Vol. 4 No. 1 (2022): 2022: Undergraduate Scholarly Showcase Proceedings.

32. Kang Jin, Daniel Schnell, Guangyuan Li, S. Prasath, R. Szczesniak, B. J. Aronow. CellDrift: Identifying cellular and temporal patterns of perturbation responses from single-cell data. Probabilistic Modelling in Genomics (ProbGen), March 2022. Poster presentation.

33. Xiaoxuan Liu, James Reigle, Erik Drysdale, Oscar Nunez-Lopez, Iram Siddiqui, Thomas Walters, Jeffrey Hyams, Lee Denson, S. Prasath, Jasbir Dhaliwal. Predicting one-year corticosteroid-free remission in pediatric ulcerative colitis with interpretable machine learning. Digestive Health Center (DHC) Annual Scientific Symposium, Cincinnati, USA, February 2022.

34. Qingqing Wu, Jizhou Zhang, Courtney Johnson, Benjamin Weinhaus, Anastasiya Slaughter, Andre Valladares-Nuez, Andre Sherman, Marie-Dominique Filippi, S. Prasath, Sing Sing Way, J. Mathew Koffron, Daniel Lucas-Alcaraz. A durable anatomy with local plasticity enables normal and stress hematopoiesis. 63rd Annual American Society of Hematology (ASH) Meeting. Blood, vol 138 (Supplement 1): 297, November 2021. doi:10.1182/blood-2021-153083

35. Daiki Katsuma, H. Kawanaka, B. J. Aronow, V. B. S. Prasath. The effects of augmentation using GAN for confocal immunofluorescence image segmentation. 10th International Conference on Informatics, Electronics and Vision (ICIEV), Fukuoka, Japan, August 2021. (Work-in-Progress Best Paper Award)

36. Guangyuan Li, Song Baobao, H.L. Grimes, V. B. S. Prasath, Nathan Salomonis. scTriangulate - Decision-level integration of multimodal single-cell data. Single Cell Analyses, CSHL, November 2021. Poster presentation.

37. Tareian Cazares, Faiz Rizvi, Balaji Iyer, Xiaoting Chen, Michael Kotliar, Leah C. Kottyan, Artem Barski, S. Prasath, Matthew T. Weirauch and Emily R. Miraldi. maxATAC: A suite of user-friendly, deep neural network models for transcription factor binding prediction from ATAC-seq. Great Lakes Bioinformatics Conference (GLBIO), May 2021.

38. Manan Shah, Derek Shu, Yizhao Ni, S. Prasath, Andrew Schapiro, Kevin Dufendach. Feasibility of machine learning to automatically extract PICC tip locations from unstructured radiology reports. Pediatric Academic Societies (PAS) Virtual Meeting, May 2021.

39. Smruti Deoghare, Ravi Yadav, Leah A. Gilligan, V. B. S. Prasath, Andrew T. Trout, Jonathan R. Dillman. Deep learning predicts ultrasound SWE liver stiffness in children. 106th RSNA Annual Meeting, 29 November - 5 December 2020. Virtual presentation.

40. Manan Shah, Yizhao Ni, S. Prasath, Andrew Schapiro, Kevin Dufendach. Machine learning to identify peripherally inserted central catheter (PICC) tip position from radiology reports. American Medical Informatics Association (AMIA) Annual Symposium, Chicago, USA, November 2020. Virtual presentation.

41. Manan Shah, Kevin Dufendach, Andrew Schapiro, Yizhao Ni, S. Prasath. Comparison of various machine learning models to identify peripherally inserted central catheter (PICC) tip position from radiology reports. American Academy of Pediatrics (AAP) Virtual National Conference and Exhibition, San Diego, USA, October 2020. Virtual Presentation. doi:10.1542/peds.147.3MA1.6b 

42. Alejandra María Casar Berazaluce, Ravi Yadav, Smruti Deoghare, Alexander Gibbons, V. B. S. Prasath, Todd A. Ponsky, B. A. Rymeski. Artificial intelligence driven automated detection of pyloric stenosis in ultrasound imaging. International Pediatric Endosurgery Group (IPEG), Vienna, Austria, June 2020. Virtual presentation.

43. Faiz Rizvi, Tareian Cazares, Balaji Iyer, Matthew T. Weirauch, Leah Kottyan, S. Prasath, Emily R. Miraldi. Using deep learning to predict cell type-specific chromatin accessibility based on genotype alone. 12th annual RECOMB/ISCB Conference on Regulatory and Systems Genomics, New York, USA, November 2019. Poster presentation.

44. Balaji Iyer, Smruti Deoghare, Samuel Hacker, Vivek Khandwala, David Wang, Daniel Woo, Achala S. Vagal, V. B. S. Prasath. Predicting ICH patient outcome from brain CT scans using an ensemble deep learning framework. Advanced Computational Neuroscience Network (ACNN), University of Michigan, Ann Arbor, MI, USA, 19 - 20 September, 2019.

45. Samuel W. Hacker, Balaji Iyer, Smruti Deoghare, Vivek J. Khandwala, David Wang, Daniel Woo, Achala S. Vagal, V. B. S.Prasath. Automated ICH outcome prediction from CT scans by ensemble convolutional neural network architecture. Capstone Poster Symposium, University of Cincinnati, Cincinnati, OH, USA, July 2019. (Second Best Poster Award)

46. Faiz Rizvi, Tareian Cazares, Joseph Wayman, S. Prasath, E. Miraldi. Flexible, scalable methods to infer transcriptional regulatory networks from single-cell genomics data. CCHMC Developmental Biology Retreat, June 2019.

47. Faiz Rizvi, Tareian Cazares, Balaji Iyer, Matthew T. Weirauch, Leah Kottyan, S. Prasath, E. Miraldi. Using deep learning to predict cell type-specific chromatin accessibility based on genotype alone. CCHMC Immunology Retreat, April 2019.

48. Harshith Bondada, V. B. S. Prasath. Mosaicking and blending in large-scale neuroimaging for robust dendrite detection. Carnegie Mellon Forum on Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA, 21 September 2018. Poster presentation.

49. V. B. S. Prasath. Shape reconstruction for endoscopy with robust perspective shape from shading. Carnegie Mellon Forum on Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA, 21 September 2018. Poster presentation.

50. Srinivasa Siddhartha Selagamsetty, V. B. S. Prasath. Human epithelial type-2 cell segmentation with deep convolutional neural networks. Carnegie Mellon Forum on Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA, 21 September 2018. Poster presentation.

51. Asami Yonekura, H. Kawanaka, V. B. S. Prasath, B. J. Aronow, H. Takase. Automatic disease stage classification of brain Glioblastoma Multiforme histopathological images using deep convolutional neural networks. Machine Learning in Science and Engineering, Carnegie Mellon University, Pittsburgh, PA, USA, 6 - 8 June, 2018. Poster presentation. Available at figshare: doi:10.6084/m9.figshare.6394889

52. Y. M. Kassim, V. B. S. Prasath, O. Glinskii, V. Glinsky, V. Huxley, K. Palaniappan. Deep CNN segmentation for epifluorescence microscopy images. Machine Learning in Science and Engineering, Carnegie Mellon University, Pittsburgh, PA, USA, 6 - 8 June, 2018. Poster presentation. Available at figshare: doi:10.6084/m9.figshare.6390590

53. A. Yonekura, H. Kawanaka, V. B. S. Prasath, B. J. Aronow, H. Takase. Disease stage classification for Glioblastoma Multiforme histopathological images using deep convolutional neural network. Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS), Otsu, Japan, June 2017.

54. Y. M. Kassim, V. B. S. Prasath, O. Glinskii, V. Glinsky, V. Huxley, K. Palaniappan. Epifluorescence vessel structure segmentation with optimized feature bank and random forests. Missouri Life Sciences Week, 10 April 2017, University of Missouri-Columbia, USA. Poster presentation.

55. K. Fukuma, H. Kawanaka, S. Prasath, B. Aronow, H. Takase. A proposal of new segmentation method for glioma pathology images. 7th International Workshop on Regional Innovation Studies (IWRIS), Mie, Japan, October 2016. (Outstanding Paper Award)

56. V. B. S. Prasath, R. Pelapur, Y. M. Kassim, O. Glinskii, V. Glinsky, V. Huxley, K. Palaniappan. Computerized microvascular dura mater structure extraction from confocal microscopy images. Missouri Life Sciences Week, 18 April 2016, University of Missouri-Columbia, USA. Poster presentation.

57. S. Meena, V. B. S. Prasath, Y. M. Kassim, R. Pelapur, O. Glinskii, V. Glinsky, V. Huxley, K. Palaniappan. Multiquadrics based interactive segmentation of dura mater microvasculature from epifluorescence images. Missouri Life Sciences Week, 18 April 2016, University of Missouri-Columbia, USA. Poster presentation.

58. Y. M. Kassim, V. B. S. Prasath, R. Pelapur, O. Glinskii, V. Glinsky, V. Huxley, K. Palaniappan. Improved random forests for dura mater microvasculature segmentation using epifluorescence images. Missouri Life Sciences Week, 18 April 2016, University of Missouri-Columbia, USA.  Poster presentation.

59. V. B. S. Prasath, R. Pelapur, Y. M. Kassim, S. Meena, A. Palaniappan, U. Sampathkumar, O. Glinskii, V. Glinsky, V. Huxley, K. Palaniappan. Computerized microvasculature dura mater structure extraction and analysis of fluorescence microscopy imagery. Missouri Informatics Symposium, 4 April 2016, University of Missouri-Columbia, USA. Poster presentation. Available at figshare: doi:10.6084/m9.figshare.3146269.v1

60. K. Fukuma, H. Kawanaka, S. Prasath, B. Aronow, H. Takase. A study on nuclei segmentation accuracy for tissue specimen analysis of brain histopathology images. 7th International Workshop on Regional Innovation Studies (IWRIS), Mie, Japan, pp. 21–24, 2015. 

61. V. B. S. Prasath, R. Pelapur, O. Glinskii, V. Glinsky, V. Huxley, K. Palaniappan. Multiscale anisotropic tensor filtering of fluorescence microscopy for denoising vasculature. Missouri Life Sciences Week, 13 April 2015, University of Missouri-Columbia, USA. Poster presentation. Available at figshare: doi:10.6084/m9.figshare.1309773

62. V. B. S. Prasath. Shearlet active contours. February Fourier Talks (FFT), February 2015, University of Maryland, MD, USA. Poster presentation.

63. V. B. S. Prasath, R. Pelapur, K. Palaniappan. Multi-scale directional vesselness stamping based segmentation for polyps from wireless capsule endoscopy. 36th Annual International Conference of the Engineering in Medicine and Biology Society (IEEE EMBC), Chicago, IL, USA, August 2014. Late breaking research posters paper. Also in: Missouri Life Sciences Week, 13 April 2015. Poster presentation. Available at figshare: doi:10.6084/m9.figshare.1087896

64. V. B. S. Prasath, F. Bunyak, P. Dale, S. R. Frazier, K. Palaniappan. Stromal-epithelial separation for breast cancer tissue microarrays from histopathology. Missouri Life Sciences Week, 14 April 2014, University of Missouri-Columbia, USA. Poster presentation. Available at figshare: doi:10.6084/m9.figshare.997514

65. V. B. S. Prasath. Geometric separation using Shearlets: Application to road line extraction and vessel segmentation. February Fourier Talks (FFT), February 2014, University of Maryland, MD, USA. Poster presentation.

66. V. B. S. Prasath, J. C. Moreno. On convergent finite difference schemes for variational PDE based image processing. First Central Region Conference on Numerical Analysis and Dynamical Systems, May 2013, Department of Mathematics, University of Kansas, Lawrence, KS, USA. Poster presentation. Available at figshare: doi:10.6084/m9.figshare.695306

67. V. B. S. Prasath, O. Haddad, F. Bunyak, R. Singh, O. Glinskii, V. Glinsky, V. Huxley, K. Palaniappan. Computerized Dura Mater Laminae analysis of fluorescence microscopy images. Missouri Life Sciences Week, 15 April 2013, University of Missouri-Columbia, USA. Also in: Graduate Summer School, IPAM, UCLA, 26 July 2013. Poster presentation. Available at figshare: doi:10.6084/m9.figshare.661533

68. V. B. S. Prasath. Efficient splitting techniques for adaptive total variation based image decomposition. February Fourier Talks (FFT), February 2013, University of Maryland, USA. Poster presentation.

69. D. Vorotnikov, V. B. S. Prasath. Global dissipative solutions of a coupled problem for image restoration. Workshop on Nonlinear Partial Differential Equations (on the occasion of the sixtieth birthday of Patrizia Pucci), 28 May - 1 June 2012, Perugia, Italy. Poster presentation.

70. I. N. Figueiredo, V. B. S. Prasath, Y.-H. R. Tsai, P. N. Figueiredo. Human colorectal polyp detection from wireless capsule endoscopy images. 7th International Congress on Industrial and Applied Mathematics (ICIAM), Vancouver, BC, Canada, July 2011.

71. J. C. Moreno, I. N. Figueiredo, V. B. S. Prasath. Texture image segmentation using higher order derivatives. Congress on Numerical Methods in Engineering (CMNE), Coimbra, Portugal, June 2011. Full paper appeared in the conference CD-ROM proceedings.

72. V. B. S. Prasath, I. N. Figueiredo, P. N. Figueiredo. Colonic mucosa detection in wireless capsule endoscopic images and videos. Congress on Numerical Methods in Engineering (CMNE), Coimbra, Portugal, June 2011. Full paper appeared in the conference CD-ROM proceedings.

73. I. N. Figueiredo, V. B. S. Prasath, Y.-H. R. Tsai, P. N. Figueiredo. Geometry based polyp detection in wireless capsule endoscopy images. IMA Annual Program Year Workshop: Computing in Image Processing, Computer Graphics, Virtual Surgery, and Sports, IMA - University of Minnesota, USA, March 2011. Poster presentation.

74. J. C. Moreno, V. B. S. Prasath, I. N. Figueiredo, G. Stadler. A new segmentation model for endoscopic human colonic aberrant crypt foci. Summer School and Work- shop on Imaging Sciences and Medical Imaging (ISMA), Coimbra, Portugal, June 2010. Poster presentation.

75. V. B. S. Prasath. Nonlinear partial differential equations in computer vision. International Conference on Mathematics and Computer Science (ICMCS), Chennai, India, January 2009.

76. V. B. S. Prasath. Robust M-estimators in early computer vision problems. International Conference On New Trends in Statistics and Optimization (ICONTSO), Kashmir, India, October 2008.

Book Chapters:

1. M. M. S. Missen, M. Coustaty, H. Asmat, A. Firdous, N. Akhtar, M. Akram, V. B. S. Prasath. 2Es of TIS: A review of information exchange and extraction in tourism information systems. Recommender System with Machine Learning and Artificial Intelligence: Practical Tools and Applications in Medical and Agricultural and Other Industries (eds.: S. N. Mohanty et al.), 45-70, 2020. Invited paper. doi:10.1002/9781119711582.ch3

2. N. Iqbal, M. M. S. Missen, N. Salamat, V. B. S. Prasath. On video based human abnormal activity detection with histogram of oriented gradients. Handbook of Multimedia Information Security: Techniques and Applications (eds.: A. K. Singh, A. Mohan), 431-438, Springer, Berlin, July 2019. Invited paper. doi:10.1007/978-3-030-15887-3_21

3. M. F. Ferdous, P. Tiwari, V. B. S. Prasath. Design and construction of a light-detecting and obstacle-sensing robot for IoT - Preliminary feasibility study. Handbook of Internet of Things and Big Data (eds.: V. K. Solanki, V. G. Diaz, P. J. Davim), 59-79, CRC Press, Taylor & Francis, USA, March 2019. Invited paper. doi:10.1201/9780429053290-3

Student Theses:

1. Smruti P. Deoghare. Deep Learning based Computer Aided Decision (CAD) Systems for Multimodal Biomedical Imaging. PhD Thesis, Division of Biomedical Informatics, CCHMC, Department of Biomedical Informatics, University of Cincinnati, USA, 2024.

2. Xiaoxuan Liu. Interpretable Machine Learning for Histopathology Images Classification in Pediatric Ulcerative Colitis Remission Prediction. MS Thesis, Department of Computer Science, University of Cincinnati, USA, 2022.

3. Lei Liu. Leveraging Machine Learning for Pattern Discovery and Decision Optimization on Last-minute Surgery Cancellation., Division of Biomedical Informatics, CCHMC, Department of Biomedical Informatics, University of Cincinnati, USA, 2021.

4. Srinivasa Siddhartha Selagamsetty. Exploring a Methodology for Segmenting Biomedical Images using Deep Learning. MS Thesis, Electrical Engineering and Computer Science, University of Cincinnati, USA, 2019.

5. Harshith Bondada. Retinal Vessel Segmentation on Ultra Wide-field Fluorescein Angiography Images. MS Thesis, Electrical Engineering and Computer Science, University of Cincinnati, USA, 2019.

6. Okubo Shunsuke. Skeleton-Based Gait Assessment Using Deep Learning for Cerebral Palsy. MS Thesis, Mie University, Japan, 2023.

7. Ginga Sumi. Gait Quality Assessment Using Unsupervised Deep Learning Model for Cerebral Palsy. MS Thesis, Mie University, Japan 2023.