Reproducibility of the coronary calcium measurement with different cardiac algorithms using multislice spiral CT. - Yun Liang 008; Ganapathy Krishnamurthi; Laigao Michael Chen; Cristopher A. Meyer (Image Processing, 2002)

Functional imaging in small animals using X-ray computed Tomography -study of physiologic measurement reproducibility. - Ganapathy Krishnamurthi; Keith M. Stantz; Rosemary Steinmetz; Vincent H. Gattone; Minsong Cao; Gary D. Hutchins; Yun Liang 008 (IEEE Trans. Medical Imaging, 2005)

Automated analysis of label-free spinning-disc microarray images. - Ganapathy Krishnamurthi; Tim Norwood; Manoj Varma (Image Processing: Algorithms and Systems, 2008)

Atheromatic™: Symptomatic vs. asymptomatic classification of carotid ultrasound plaque using a combination of HOS, DWT & texture. - U. Rajendra Acharya; Oliver Faust; Subbhuraam Vinitha Sree; Peng Chuan Alvin Ang; Ganapathy Krishnamurthi; José C. R. Seabra; João M. Sanches; Jasjit S. Suri (EMBC, 2011)

Cryo-imaging of 70+GB mice: Image processing/visualization challenges and biotechnology applications. - David L. Wilson; Madhusudhana Gargesha; Debashish Roy; Mohammed Q. Qutaish; Ganapathi Krishnamurthi; Kristin Sullivant; Patiwet Wuttisarnwattana; Hong Lu 002; Benjamin Moore; Christian Anderson (ISBI, 2011)

Hypothesis Validation of Far-Wall Brightness in Carotid-Artery Ultrasound for Feature-Based IMT Measurement Using a Combination of Level-Set Segmentation and Registration. - Filippo Molinari; Ganapathy Krishnamurthi; U. Rajendra Acharya; Subbhuraam Vinitha Sree; Guang Zeng; Luca Saba; Andrew Nicolaides; Jasjit S. Suri (IEEE Trans. Instrum. Meas., 2012)

Understanding symptomatology of atherosclerotic plaque by image-based tissue characterization. - U. Rajendra Acharya; Oliver Faust; Subbhuraam Vinitha Sree; Peng Chuan Alvin Ang; Ganapathy Krishnamurthi; José C. R. Seabra; João M. Sanches; Jasjit S. Suri (Comput. Methods Programs Biomed., 2013)

Supervised Segmentation of Polycystic Kidneys: a New Application for Stereology Data. - Joshua D. Warner; Maria V. Irazabal; Ganapathy Krishnamurthi; Bernard F. King; Vicente E. Torres; Bradley J. Erickson (J. Digit. Imaging, 2014)

Multi-modal Brain Tumor Segmentation Using Stacked Denoising Autoencoders. - Kiran Vaidhya; Subramaniam Thirunavukkarasu; Alex Varghese; Ganapathy Krishnamurthi (Brainles@MICCAI, 2015)

Segmentation and Tracking of Myocardial Boundaries Using Dynamic Programming. - Athira J. Jacob; Alex Varghese; Ganapathy Krishnamurthi (STACOM@MICCAI, 2016)

Semi-supervised Learning using Denoising Autoencoders for Brain Lesion Detection and Segmentation. - Alex Varghese; Kiran Vaidhya; Subramaniam Thirunavukkarasu; Chandrasekharan Kesavdas; Ganapathy Krishnamurthi (CoRR, 2016)

Densely Connected Fully Convolutional Network for Short-Axis Cardiac Cine MR Image Segmentation and Heart Diagnosis Using Random Forest. - Mahendra Khened; Alex Varghese; Ganapathy Krishnamurthi (STACOM@MICCAI, 2017)

Brain Tumor Segmentation Using Dense Fully Convolutional Neural Network. - Mazhar Shaikh; Ganesh Anand; Gagan Acharya; Abhijit Amrutkar; Alex Varghese; Ganapathy Krishnamurthi (BrainLes@MICCAI, 2017)

Automatic Segmentation and Overall Survival Prediction in Gliomas Using Fully Convolutional Neural Network and Texture Analysis. - Alex Varghese; Mohammed Safwan K. P.; Ganapathy Krishnamurthi (BrainLes@MICCAI, 2017)

Generative adversarial networks for brain lesion detection. - Alex Varghese; Mohammed Safwan K. P.; Sai Saketh Chennamsetty; Ganapathy Krishnamurthi (Image Processing, 2017)

Estimation of myocardial deformation using correlation image velocimetry. - Athira J. Jacob; Ganapathy Krishnamurthi; Manikandan Mathur (BMC Medical Imaging, 2017)

Fully Automatic Segmentation for Ischemic Stroke Using CT Perfusion Maps. - Vikas Kumar Anand; Mahendra Khened; Alex Varghese; Ganapathy Krishnamurthi (BrainLes@MICCAI (1), 2018)

A Combined Radio-Histological Approach for Classification of Low Grade Gliomas. - Aditya Bagari; Ashish Kumar 004; Avinash Kori; Mahendra Khened; Ganapathy Krishnamurthi (BrainLes@MICCAI (1), 2018)

Ensemble of Fully Convolutional Neural Network for Brain Tumor Segmentation from Magnetic Resonance Images. - Avinash Kori; Mehul Soni; B. Pranjal; Mahendra Khened; Alex Varghese; Ganapathy Krishnamurthi (BrainLes@MICCAI (2), 2018)

2D-Densely Connected Convolution Neural Networks for automatic Liver and Tumor Segmentation. - Krishna Chaitanya Kaluva; Mahendra Khened; Avinash Kori; Ganapathy Krishnamurthi (CoRR, 2018)

Enhanced Image Classification With Data Augmentation Using Position Coordinates. - Avinash Kori; Ganapathy Krishnamurthi; Balaji Srinivasan (CoRR, 2018)

Enhanced Optic Disk and Cup Segmentation with Glaucoma Screening from Fundus Images using Position encoded CNNs. - Vismay Agrawal; Avinash Kori; Alex Varghese; Ganapathy Krishnamurthi (CoRR, 2018)

Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved? - Olivier Bernard 001; Alain Lalande; Clément Zotti; Frederic Cervenansky; Xin Yang 009; Pheng-Ann Heng; Irem Cetin; Karim Lekadir; Oscar Camara 001; Miguel Ángel González Ballester; Gerard Sanroma; Sandy Napel; et al. (IEEE Trans. Medical Imaging, 2018)

NTIRE 2019 Challenge on Image Enhancement: Methods and Results. - Andrey Ignatov; Radu Timofte; Xiaochao Qu; Xingguang Zhou; Ting Liu; Pengfei Wan 001; Syed Waqas Zamir; Aditya Arora; Salman H. Khan 001; Fahad Shahbaz Khan; Ling Shao 001; Dongwon Park; et al. (CVPR Workshops, 2019)

Recurrent Attention Mechanism Networks for Enhanced Classification of Biomedical Images. - Mazhar Shaikh; Varghese Alex Kollerathu; Ganapathy Krishnamurthi (ISBI, 2019)

Zero Shot Learning for Multi-Modal Real Time Image Registration. - Avinash Kori; Ganapathi Krishnamurthi (CoRR, 2019)

Demystifying Brain Tumour Segmentation Networks: Interpretability and Uncertainty Analysis. - Parth Natekar; Avinash Kori; Ganapathy Krishnamurthi (CoRR, 2019)

Fully convolutional multi-scale residual DenseNets for cardiac segmentation and automated cardiac diagnosis using ensemble of classifiers. - Mahendra Khened; Alex Varghese; Ganapathy Krishnamurthi (Medical Image Anal., 2019)

Brain Tumor Segmentation and Survival Prediction Using Automatic Hard Mining in 3D CNN Architecture. - Vikas Kumar Anand; Sanjeev Grampurohit; Pranav Aurangabadkar; Avinash Kori; Mahendra Khened; Raghavendra S. Bhat; Ganapathy Krishnamurthi (BrainLes@MICCAI (2), 2020)

A Generalized Deep Learning Framework for Whole-Slide Image Segmentation and Analysis. - Mahendra Khened; Avinash Kori; Haran Rajkumar; Balaji Srinivasan; Ganapathy Krishnamurthi (CoRR, 2020)

2018 Robotic Scene Segmentation Challenge. - Max Allan; Satoshi Kondo; Sebastian Bodenstedt; Stefan Leger; Rahim Kadkhodamohammadi; Imanol Luengo; Félix Fuentes-Hurtado; Evangello Flouty; Ahmed Kedir Mohammed; Marius Pedersen; Avinash Kori; Alex Varghese; et al. (CoRR, 2020)

Structurally aware bidirectional unpaired image to image translation between CT and MR. - Vismay Agrawal; Avinash Kori; Vikas Kumar Anand; Ganapathy Krishnamurthi (CoRR, 2020)

Distangling Biological Noise in Cellular Images with a focus on Explainability. - Manik Sharma; Ganapathy Krishnamurthi (CoRR, 2020)

Abstracting Deep Neural Networks into Concept Graphs for Concept Level Interpretability. - Avinash Kori; Parth Natekar; Ganapathy Krishnamurthi; Balaji Srinivasan (CoRR, 2020)

Demystifying Brain Tumor Segmentation Networks: Interpretability and Uncertainty Analysis. - Parth Natekar; Avinash Kori; Ganapathy Krishnamurthi (Frontiers Comput. Neurosci., 2020)

A Study on Criteria for Training Collaborator Selection in Federated Learning. - Vishruth Shambhat; Akansh Maurya; Shubham Subhas Danannavar; Rohit Kalla; Vikas Kumar Anand; Ganapathy Krishnamurthi (BrainLes@MICCAI (2), 2021)

Corrigendum: Demystifying Brain Tumor Segmentation Networks: Interpretability and Uncertainty Analysis. - Parth Natekar; Avinash Kori; Ganapathy Krishnamurthi (Frontiers Comput. Neurosci., 2021)

PAIP 2019: Liver cancer segmentation challenge. - Yoo Jung Kim; Hyungjoon Jang; Kyoungbun Lee; Seongkeun Park; Sung-Gyu Min; Choyeon Hong; Jeong Hwan Park; Kanggeun Lee; Jisoo Kim; Wonjae Hong; Hyun Jung; Yanling Liu; et al. (Medical Image Anal., 2021)

PARSE challenge 2022: Pulmonary Arteries Segmentation using Swin U-Net Transformer(Swin UNETR) and U-Net. - Akansh Maurya; Kunal Dashrath Patil; Rohan Padhy; Kalluri Ramakrishna; Ganapathy Krishnamurthi (CoRR, 2022)

DigestPath: A benchmark dataset with challenge review for the pathological detection and segmentation of digestive-system. - Qian Da; Xiaodi Huang; Zhongyu Li 002; Yanfei Zuo; Chenbin Zhang; Jingxin Liu; Wen Chen 001; Jiahui Li 005; Dou Xu; Zhiqiang Hu; Hongmei Yi; Yan Guo; et al. (Medical Image Anal., 2022)

Parse Challenge 2022: Pulmonary Arteries Segmentation Using Swin U-net Transformer(Swin UNETR) and U-net. - Rohan Padhy; Akansh Maurya; Kunal Dasharath Patil; Kalluri Ramakrishna; Ganapathy Krishnamurthi (ISBI, 2023)

PICS in Pics: Physics Informed Contour Selection for Rapid Image Segmentation. - Vikas Dwivedi; Balaji Srinivasan; Ganapathy Krishnamurthi (CoRR, 2023)

The Liver Tumor Segmentation Benchmark (LiTS). - Patrick Bilic; Patrick Ferdinand Christ; Hongwei Li 004; Eugene Vorontsov; Avi Ben-Cohen; Georgios Kaissis; Adi Szeskin; Colin Jacobs; Gabriel Efrain Humpire Mamani; Gabriel Chartrand; Fabian Lohöfer; Julian Walter Holch; et al. (Medical Image Anal., 2023)

Efficient Knowledge Distillation of SAM for Medical Image Segmentation. - Kunal Dasharath Patil; Gowthamaan Palani; Ganapathy Krishnamurthi (CoRR, 2025)

Eig-PIELM: A Mesh-Free Approach for Efficient Eigen-Analysis with Physics-Informed Extreme Learning Machines. - Rishi Mishra; Smriti; Ganapathy Krishnamurthi; Balaji Srinivasan; Sundararajan Natarajan (CoRR, 2025)