| GANs for medical image analysis S Kazeminia, C Baur, A Kuijper, B van Ginneken, N Navab, S Albarqouni, ... Artificial Intelligence in Medicine 109, 101938, 2020 | 379 | 2020 |
| Knee menisci segmentation using convolutional neural networks: data from the osteoarthritis initiative A Tack, A Mukhopadhyay, S Zachow Osteoarthritis and cartilage 26 (5), 680-688, 2018 | 109 | 2018 |
| CATARACTS: Challenge on automatic tool annotation for cataRACT surgery H Al Hajj, M Lamard, PH Conze, S Roychowdhury, X Hu, G Maršalkaitė, ... Medical image analysis 52, 24-41, 2019 | 102 | 2019 |
| Statistical shape modeling of the left ventricle: myocardial infarct classification challenge A Suinesiaputra, P Ablin, X Alba, M Alessandrini, J Allen, W Bai, S Cimen, ... IEEE journal of biomedical and health informatics 22 (2), 503-515, 2017 | 83 | 2017 |
| Tool and phase recognition using contextual CNN features M Sahu, A Mukhopadhyay, A Szengel, S Zachow arXiv preprint arXiv:1610.08854, 2016 | 54 | 2016 |
| Addressing multi-label imbalance problem of surgical tool detection using CNN M Sahu, A Mukhopadhyay, A Szengel, S Zachow International journal of computer assisted radiology and surgery 12, 1013-1020, 2017 | 52 | 2017 |
| Toward an automatic preoperative pipeline for image-guided temporal bone surgery J Fauser, I Stenin, M Bauer, WH Hsu, J Kristin, T Klenzner, J Schipper, ... International journal of computer assisted radiology and surgery 14, 967-976, 2019 | 37 | 2019 |
| GaNDLF: the generally nuanced deep learning framework for scalable end-to-end clinical workflows S Pati, SP Thakur, İE Hamamcı, U Baid, B Baheti, M Bhalerao, O Güley, ... Communications Engineering 2 (1), 23, 2023 | 35* | 2023 |
| Endo-sim2real: Consistency learning-based domain adaptation for instrument segmentation M Sahu, R Strömsdörfer, A Mukhopadhyay, S Zachow International Conference on Medical Image Computing and Computer-Assisted …, 2020 | 35 | 2020 |
| An efficient Riemannian statistical shape model using differential coordinates: With application to the classification of data from the Osteoarthritis Initiative C von Tycowicz, F Ambellan, A Mukhopadhyay, S Zachow Medical image analysis 43, 1-9, 2018 | 35 | 2018 |
| Generative adversarial networks: A primer for radiologists JM Wolterink, A Mukhopadhyay, T Leiner, TJ Vogl, AM Bucher, I Išgum Radiographics 41 (3), 840-857, 2021 | 32 | 2021 |
| M3d-CAM: A PyTorch library to generate 3D attention maps for medical deep learning K Gotkowski, C Gonzalez, A Bucher, A Mukhopadhyay Bildverarbeitung für die Medizin 2021: Proceedings, German Workshop on …, 2021 | 31 | 2021 |
| Detecting when pre-trained nnu-net models fail silently for covid-19 lung lesion segmentation C Gonzalez, K Gotkowski, A Bucher, R Fischbach, I Kaltenborn, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 26 | 2021 |
| Habitat-Net: Segmentation of habitat images using deep learning JF Abrams, A Vashishtha, ST Wong, A Nguyen, A Mohamed, S Wieser, ... Ecological informatics 51, 121-128, 2019 | 25 | 2019 |
| i3PosNet: instrument pose estimation from X-ray in temporal bone surgery D Kügler, J Sehring, A Stefanov, I Stenin, J Kristin, T Klenzner, J Schipper, ... International journal of computer assisted radiology and surgery 15, 1137-1145, 2020 | 24* | 2020 |
| Planning nonlinear access paths for temporal bone surgery J Fauser, G Sakas, A Mukhopadhyay International journal of computer assisted radiology and surgery 13, 637-646, 2018 | 24 | 2018 |
| A survey on shape-constraint deep learning for medical image segmentation S Bohlender, I Oksuz, A Mukhopadhyay IEEE Reviews in Biomedical Engineering, 2021 | 22 | 2021 |
| Unsupervised myocardial segmentation for cardiac BOLD I Oksuz, A Mukhopadhyay, R Dharmakumar, SA Tsaftaris IEEE transactions on medical imaging 36 (11), 2228-2238, 2017 | 21 | 2017 |
| Simulation-to-real domain adaptation with teacher–student learning for endoscopic instrument segmentation M Sahu, A Mukhopadhyay, S Zachow International journal of computer assisted radiology and surgery 16 (5), 849-859, 2021 | 18 | 2021 |
| Total variation random forest: Fully automatic mri segmentation in congenital heart diseases A Mukhopadhyay Reconstruction, Segmentation, and Analysis of Medical Images: First …, 2017 | 18 | 2017 |
Camila GonzálezStanford UniversityVerified email at stanford.edu
