| UNet++: A nested U-Net architecture for medical image segmentation Z Zhou, MMR Siddiquee, N Tajbakhsh, J Liang Deep learning in medical image analysis and multimodal learning for clinical …, 2018 | 6603 | 2018 |
| Convolutional neural networks for medical image analysis: Full training or fine tuning? N Tajbakhsh, JY Shin, SR Gurudu, RT Hurst, CB Kendall, MB Gotway, ... IEEE transactions on medical imaging 35 (5), 1299-1312, 2016 | 3248 | 2016 |
| UNet++: Redesigning skip connections to exploit multiscale features in image segmentation Z Zhou, MMR Siddiquee, N Tajbakhsh, J Liang IEEE transactions on medical imaging 39 (6), 1856-1867, 2019 | 2562 | 2019 |
| Automated polyp detection in colonoscopy videos using shape and context information N Tajbakhsh, SR Gurudu, J Liang IEEE transactions on medical imaging 35 (2), 630-644, 2015 | 736 | 2015 |
| Fine-tuning convolutional neural networks for biomedical image analysis: Actively and incrementally Z Zhou, J Shin, L Zhang, S Gurudu, M Gotway, J Liang Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 476 | 2017 |
| Comparative validation of polyp detection methods in video colonoscopy: results from the MICCAI 2015 endoscopic vision challenge J Bernal, N Tajkbaksh, FJ Sanchez, BJ Matuszewski, H Chen, L Yu, ... IEEE transactions on medical imaging 36 (6), 1231-1249, 2017 | 393 | 2017 |
| Models Genesis: Generic autodidactic models for 3D medical image analysis Z Zhou, V Sodha, MMR Siddiquee, R Feng, N Tajbakhsh, MB Gotway, ... International conference on medical image computing and computer-assisted …, 2019 | 310 | 2019 |
| Models Genesis Z Zhou, V Sodha, J Pang, MB Gotway, J Liang Medical image analysis 67, 101840, 2021 | 261 | 2021 |
| Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study RD Rudyanto, S Kerkstra, EM Van Rikxoort, C Fetita, PY Brillet, C Lefevre, ... Medical image analysis 18 (7), 1217-1232, 2014 | 173 | 2014 |
| Automatic polyp detection in colonoscopy videos using an ensemble of convolutional neural networks N Tajbakhsh, SR Gurudu, J Liang 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 79-83, 2015 | 168 | 2015 |
| Computer-aided pulmonary embolism detection using a novel vessel-aligned multi-planar image representation and convolutional neural networks N Tajbakhsh, MB Gotway, J Liang Medical Image Computing and Computer-Assisted Intervention--MICCAI 2015 …, 2015 | 160 | 2015 |
| United snakes J Liang, T McInerney, D Terzopoulos Medical image analysis 10 (2), 215-233, 2006 | 152 | 2006 |
| Computer-aided detection (CAD) for CT colonography: a tool to address a growing need L Bogoni, P Cathier, M Dundar, A Jerebko, S Lakare, J Liang, ... The British Journal of Radiology 78 (suppl_1), S57-S62, 2005 | 125 | 2005 |
| Learning fixed points in generative adversarial networks: From image-to-image translation to disease detection and localization MMR Siddiquee, Z Zhou, N Tajbakhsh, R Feng, MB Gotway, Y Bengio, ... Proceedings of the IEEE/CVF international conference on computer vision, 191-200, 2019 | 106 | 2019 |
| Under-reporting of greenhouse gas emissions in US cities KR Gurney, J Liang, G Roest, Y Song, K Mueller, T Lauvaux Nature communications 12 (1), 553, 2021 | 99 | 2021 |
| Computer aided detection of pulmonary embolism with tobogganing and mutiple instance classification in CT pulmonary angiography J Liang, J Bi Biennial International Conference on Information Processing in Medical …, 2007 | 95 | 2007 |
| Automatic sky view factor estimation from street view photographs—A big data approach J Liang, J Gong, J Sun, J Zhou, W Li, Y Li, J Liu, S Shen Remote Sensing 9 (5), 411, 2017 | 94 | 2017 |
| Transferable visual words: Exploiting the semantics of anatomical patterns for self-supervised learning F Haghighi, MRH Taher, Z Zhou, MB Gotway, J Liang IEEE transactions on medical imaging 40 (10), 2857-2868, 2021 | 93 | 2021 |
| Medical diagnostic ultrasound characterization of cardiac motion J Liang, S Krishnan, R Rao US Patent App. 11/184,598, 2006 | 93 | 2006 |
| Surrogate supervision for medical image analysis: Effective deep learning from limited quantities of labeled data N Tajbakhsh, Y Hu, J Cao, X Yan, Y Xiao, Y Lu, J Liang, D Terzopoulos, ... 2019 IEEE 16th international symposium on biomedical imaging (ISBI 2019 …, 2019 | 90 | 2019 |
Nima TajbakhshNvidia Inc.在 asu.edu 的电子邮件经过验证
