| & Chintala, S.(2019) A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... Pytorch: An imperative style, high-performance deep learning library …, 0 | 10 | |
| 2D-3D fully convolutional neural networks for cardiac MR segmentation J Patravali, S Jain, S Chilamkurthy Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS …, 2018 | 141 | 2018 |
| A 2017 guide to semantic segmentation with deep learning S Chilamkurthy Available at blog. qure. ai/notes/semantic-segmentation-deep-learning-review …, 2017 | 35 | 2017 |
| Advances in Neural Information Processing Systems 32 ed H A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... Wallach et al 8024, 2019 | 52 | 2019 |
| Ai improves stroke diagnosis and care at a low resource hospital in india U Upadhyay, J Webster, S Tanamala, S Chilamkurthy, S Golla, ... Journal of the Neurological Sciences 429, 2021 | 1 | 2021 |
| Automated lateral ventricular and cranial vault volume measurements in 13,851 patients using deep learning algorithms GA Maragkos, AS Filippidis, S Chilamkurthy, MM Salem, S Tanamala, ... World Neurosurgery 148, e363-e373, 2021 | 6* | 2021 |
| Automatic anatomical characterization of intracranial hemorrhage in head CT scans S Tanamala, S Chilamkurthy, R Ghosh, P Rao European Congress of Radiology-ECR 2019, 2019 | | 2019 |
| Brain Anatomy Segmentation S Chilamkurthy | | |
| Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study S Chilamkurthy, R Ghosh, S Tanamala, M Biviji, NG Campeau, ... The Lancet 392 (10162), 2388-2396, 2018 | 817 | 2018 |
| Deep learning and medical diagnosis–Authors' reply S Chilamkurthy, S Tanamala The Lancet 394 (10210), 1711, 2019 | 1 | 2019 |
| Deep learning as triage system for critical findings in head CT scans S Chilamkurthy, S Tanamala, R Ghosh, P Rao, V Mahajan European Congress of Radiology-ECR 2019, 2019 | | 2019 |
| DEEP LEARNING BASED LVO DETECTION ON CT ANGIOGRAPHY OF BRAIN S Kumar, A Agarwal, S Tanamala, S Golla, P Putha, U Upadhyay, ... INTERNATIONAL JOURNAL OF STROKE 17 (3_ SUPPL), 19-20, 2022 | | 2022 |
| Deep-aspects: A segmentation-assisted model for stroke severity measurement U Upadhyay, M Ranjan, S Golla, S Tanamala, P Sreenivas, ... European Conference on Computer Vision, 330-339, 2022 | 6 | 2022 |
| Development and validation of deep learning algorithms for detection of critical findings in head CT scans S Chilamkurthy, R Ghosh, S Tanamala, M Biviji, NG Campeau, ... arXiv preprint arXiv:1803.05854, 2018 | 119 | 2018 |
| Keras tutorial–traffic sign recognition S Chilamkurthy | 9 | 2017 |
| Machine Learning Approach to Arterial Input Function Estimation in Cerebral Perfusion Imaging R Kushawaha, S Chilamkurthy, S Golla, U Upadhyay, S Tanamala, ... INTERNATIONAL JOURNAL OF STROKE 17 (2_ SUPPL), 36-36, 2022 | | 2022 |
| Mind the Clot: Automated LVO Detection on CTA Using Deep Learning S Kumar, A Agarwal, S Golla, S Tanamala, U Upadhyay, S Chattoraj, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 1 | 2023 |
| Monitoring brain CT scan image P Putha, S Chilamkurthy, SK Golla, S Tanamala, U Upadhyay US Patent 11,636,596, 2023 | | 2023 |
| Monitoring brain CT scan image U Upadhyay, SK Golla, S Tanamala, S Chilamkurthy, P Putha US Patent 11,501,437, 2022 | 1 | 2022 |
| Morphology of the brain: changes in ventricular and cranial vault volumes in 15000 subjects with aging and hydrocephalus S Chilamkurthy, P Rao, G Maragkos, A Thomas Qure. ai, Beth Israel Deaconess Medical Center March 11, 2019 | 2 | 2019 |
