| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 2338 | 2018 |
| The liver tumor segmentation benchmark (lits) P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ... Medical image analysis 84, 102680, 2023 | 1439 | 2023 |
| Idrid: Diabetic retinopathy–segmentation and grading challenge P Porwal, S Pachade, M Kokare, G Deshmukh, J Son, W Bae, L Liu, ... Medical image analysis 59, 101561, 2020 | 326 | 2020 |
| A generalized deep learning framework for whole-slide image segmentation and analysis M Khened*, A Kori*, H Rajkumar*, G Krishnamurthi, B Srinivasan Scientific reports 11 (1), 1-14, 2021 | 188 | 2021 |
| 2018 robotic scene segmentation challenge M Allan, S Kondo, S Bodenstedt, S Leger, R Kadkhodamohammadi, ... arXiv preprint arXiv:2001.11190, 2020 | 108 | 2020 |
| Demystifying brain tumor segmentation networks: interpretability and uncertainty analysis P Natekar, A Kori, G Krishnamurthi Frontiers in computational neuroscience 14, 6, 2020 | 105 | 2020 |
| Segmentation and classification in digital pathology for glioma research: challenges and deep learning approaches T Kurc, S Bakas, X Ren, A Bagari, A Momeni, Y Huang, L Zhang, A Kumar, ... Frontiers in neuroscience 14, 27, 2020 | 86 | 2020 |
| 2D-densely connected convolution neural networks for automatic liver and tumor segmentation KC Kaluva, M Khened, A Kori, G Krishnamurthi arXiv preprint arXiv:1802.02182, 2018 | 84 | 2018 |
| Brain tumor segmentation and survival prediction using automatic hard mining in 3D CNN architecture VK Anand, S Grampurohit, P Aurangabadkar, A Kori, M Khened, RS Bhat, ... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2021 | 47 | 2021 |
| Ensemble of convolutional neural networks for automatic grading of diabetic retinopathy and macular edema A Kori, SS Chennamsetty, V Alex arXiv preprint arXiv:1809.04228, 2018 | 40 | 2018 |
| Zero shot learning for multi-modal real time image registration A Kori, G Krishnamurthi arXiv preprint arXiv:1908.06213, 2019 | 36 | 2019 |
| Robotic scene segmentation challenge M Allan, S Kondo, S Bodenstedt, S Leger, R Kadkhodamohammadi, ... arXiv preprint arXiv:2001.11190, 2018 | 29 | 2018 |
| Ensemble of fully convolutional neural network for brain tumor segmentation from magnetic resonance images A Kori, M Soni, B Pranjal, M Khened, V Alex, G Krishnamurthi International MICCAI Brainlesion Workshop, 485-496, 2018 | 23 | 2018 |
| A combined radio-histological approach for classification of low grade gliomas A Bagari*, A Kumar*, A Kori*, M Khened, G Krishnamurthi Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2019 | 15 | 2019 |
| Enhanced optic disk and cup segmentation with glaucoma screening from fundus images using position encoded CNNs V Agrawal, A Kori, V Alex, G Krishnamurthi arXiv preprint arXiv:1809.05216, 2018 | 14 | 2018 |
| Vector Quantisation for Robust Segmentation A Santhirasekaram*, A Kori*, M Winkler, A Rockall, B Glocker International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 12 | 2022 |
| Interpreting deep neural networks for medical imaging using concept graphs A Kori, P Natekar, B Srinivasan, G Krishnamurthi International Workshop on Health Intelligence, 201-216, 2021 | 9 | 2021 |
| Abstracting deep neural networks into concept graphs for concept level interpretability A Kori, P Natekar, G Krishnamurthi, B Srinivasan arXiv preprint arXiv:2008.06457, 2020 | 9 | 2020 |
| Grounded object centric learning A Kori, F Locatello, FDS Ribeiro, F Toni, B Glocker arXiv preprint arXiv:2307.09437, 2023 | 7 | 2023 |
| Glance: Global to local architecture-neutral concept-based explanations A Kori, B Glocker, F Toni arXiv preprint arXiv:2207.01917, 2022 | 6 | 2022 |
Ganapathy KrishnamurthiAssociate Professor at IIT-MadrasVerified email at iitm.ac.in
