Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs JI Orlando, H Fu, JB Breda, K Van Keer, DR Bathula, A Diaz-Pinto, ... Medical image analysis 59, 101570, 2020 | 598 | 2020 |
Psi-Net: Shape and boundary aware joint multi-task deep network for medical image segmentation B Murugesan, K Sarveswaran, SM Shankaranarayana, K Ram, J Joseph, ... 2019 41st Annual international conference of the IEEE engineering in …, 2019 | 165 | 2019 |
Joint optic disc and cup segmentation using fully convolutional and adversarial networks SM Shankaranarayana, K Ram, K Mitra, M Sivaprakasam Fetal, Infant and Ophthalmic Medical Image Analysis: International Workshop …, 2017 | 129 | 2017 |
ALIME: Autoencoder based approach for local interpretability SM Shankaranarayana, D Runje Intelligent Data Engineering and Automated Learning–IDEAL 2019: 20th …, 2019 | 125 | 2019 |
Fully convolutional networks for monocular retinal depth estimation and optic disc-cup segmentation SM Shankaranarayana, K Ram, K Mitra, M Sivaprakasam IEEE journal of biomedical and health informatics 23 (4), 1417-1426, 2019 | 81 | 2019 |
Ecgnet: Deep network for arrhythmia classification B Murugesan, V Ravichandran, K Ram, SP Preejith, J Joseph, ... 2018 IEEE International Symposium on Medical Measurements and Applications …, 2018 | 81 | 2018 |
RespNet: A deep learning model for extraction of respiration from photoplethysmogram V Ravichandran, B Murugesan, V Balakarthikeyan, K Ram, SP Preejith, ... 2019 41st annual international conference of the IEEE engineering in …, 2019 | 64 | 2019 |
Adam challenge: Detecting age-related macular degeneration from fundus images H Fang, F Li, H Fu, X Sun, X Cao, F Lin, J Son, S Kim, G Quellec, S Matta, ... IEEE transactions on medical imaging 41 (10), 2828-2847, 2022 | 52 | 2022 |
Constrained monotonic neural networks D Runje, SM Shankaranarayana International Conference on Machine Learning, 29338-29353, 2023 | 21 | 2023 |
Deep network for capacitive ECG denoising V Ravichandran, B Murugesan, SM Shankaranarayana, K Ram, ... 2019 IEEE International Symposium on Medical Measurements and Applications …, 2019 | 16 | 2019 |
Attention augmented convolutional transformer for tabular time-series SM Shankaranarayana, D Runje 2021 International Conference on Data Mining Workshops (ICDMW), 537-541, 2021 | 13 | 2021 |
Effects of refractive index mismatch in optical CT imaging of polymer gel dosimeters R Manjappa, S Makki S, R Kumar, R Kanhirodan Medical physics 42 (2), 750-759, 2015 | 12 | 2015 |
A context based deep learning approach for unbalanced medical image segmentation B Murugesan, K Sarveswaran, SM Shankaranarayana, K Ram, ... 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1949-1953, 2020 | 10 | 2020 |
Hybrid analysis framework for prediction of outcomes in clinical trials R Krishnan, J Domenech, R Jagannathan, SM Shankaranarayana US Patent 11,101,043, 2021 | 7 | 2021 |
What Role for AI in Insurance Pricing T Maynard, A Bordon, JB Berry, DB Baxter, W Skertic, BTMK Gotch, ... A PREPRINT, 2019 | 6 | 2019 |
Restoration of neonatal retinal images SM Shankaranarayana, K Ram, A Vinekar, K Mitra, M Sivaprakasam Proceedings of the Ophthalmic Medical Image Analysis International Workshop …, 2016 | 6 | 2016 |
Artificial intelligence enabled assessment of damage to automobiles R Krishnan, J Domenech US Patent App. 16/587,934, 2020 | 5 | 2020 |
Conv-MCD: A plug-and-play multi-task module for medical image segmentation B Murugesan, K Sarveswaran, SM Shankaranarayana, K Ram, J Joseph, ... Machine Learning in Medical Imaging: 10th International Workshop, MLMI 2019 …, 2019 | 5 | 2019 |
Automated heuristic deep learning-based modelling R Krishnan, J Domenech, R Jagannathan, SM Shankaranarayana US Patent App. 16/590,249, 2020 | 4 | 2020 |
Joint shape learning and segmentation for medical images using a minimalistic deep network B Murugesan, K Sarveswaran, SM Shankaranarayana, K Ram, ... arXiv preprint arXiv:1901.08824, 2019 | 3 | 2019 |