| Low-dose CT image denoising using a generative adversarial network with Wasserstein distance and perceptual loss Q Yang, P Yan, Y Zhang, H Yu, Y Shi, X Mou, MK Kalra, Y Zhang, L Sun, ... IEEE transactions on medical imaging 37 (6), 1348-1357, 2018 | 1340 | 2018 |
| Deep learning in medical image registration: a survey G Haskins, U Kruger, P Yan Machine Vision and Applications 31, 1-18, 2020 | 593 | 2020 |
| Magnetic Resonance Imaging/Ultrasound Fusion Guided Prostate Biopsy Improves Cancer Detection Following Transrectal Ultrasound Biopsy and Correlates With Multiparametric … P Pinto, P Chung, A Rastinehad, A Baccala, J Kruecker, C Benjamin, S Xu, ... The Journal of Urology 186 (4), 1281-1285, 2011 | 545 | 2011 |
| Manifold regularized sparse NMF for hyperspectral unmixing X Lu, H Wu, Y Yuan, P Yan, X Li IEEE Transactions on Geoscience and Remote Sensing 51 (5), 2815-2826, 2012 | 387 | 2012 |
| Learning 4D action feature models for arbitrary view action recognition P Yan, SM Khan, M Shah 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-7, 2008 | 223 | 2008 |
| Deeply-supervised CNN for prostate segmentation Q Zhu, B Du, B Turkbey, PL Choyke, P Yan 2017 international joint conference on neural networks (IJCNN), 178-184, 2017 | 216 | 2017 |
| Automatic segmentation of high-throughput RNAi fluorescent cellular images P Yan, X Zhou, M Shah, STC Wong IEEE transactions on information technology in biomedicine 12 (1), 109-117, 2008 | 196 | 2008 |
| Boundary-weighted domain adaptive neural network for prostate MR image segmentation Q Zhu, B Du, P Yan IEEE transactions on medical imaging 39 (3), 753-763, 2019 | 186 | 2019 |
| Saliency detection by multiple-instance learning Q Wang, Y Yuan, P Yan, X Li IEEE transactions on cybernetics 43 (2), 660-672, 2013 | 178 | 2013 |
| Linear SVM classification using boosting HOG features for vehicle detection in low-altitude airborne videos X Cao, C Wu, P Yan, X Li 2011 18th IEEE international conference on image processing, 2421-2424, 2011 | 155 | 2011 |
| Discrete deformable model guided by partial active shape model for TRUS image segmentation P Yan, S Xu, B Turkbey, J Kruecker IEEE transactions on Biomedical Engineering 57 (5), 1158-1166, 2010 | 150 | 2010 |
| Learning deep similarity metric for 3D MR–TRUS image registration G Haskins, J Kruecker, U Kruger, S Xu, PA Pinto, BJ Wood, P Yan International journal of computer assisted radiology and surgery 14, 417-425, 2019 | 139 | 2019 |
| D'Amico risk stratification correlates with degree of suspicion of prostate cancer on multiparametric magnetic resonance imaging AR Rastinehad, AA Baccala, PH Chung, JM Proano, J Kruecker, S Xu, ... The Journal of urology 185 (3), 815-820, 2011 | 137 | 2011 |
| 3d model based object class detection in an arbitrary view P Yan, SM Khan, M Shah 2007 IEEE 11th International Conference on Computer Vision, 1-6, 2007 | 137 | 2007 |
| Multi-organ segmentation over partially labeled datasets with multi-scale feature abstraction X Fang, P Yan IEEE Transactions on Medical Imaging 39 (11), 3619-3629, 2020 | 136 | 2020 |
| Single-image super-resolution via local learning Y Tang, P Yan, Y Yuan, X Li International Journal of Machine Learning and Cybernetics 2, 15-23, 2011 | 126 | 2011 |
| Geometry constrained sparse coding for single image super-resolution X Lu, H Yuan, P Yan, Y Yuan, X Li 2012 IEEE Conference on Computer Vision and Pattern Recognition, 1648-1655, 2012 | 124 | 2012 |
| Segmentation of volumetric MRA images by using capillary active contour P Yan, AA Kassim Medical Image Analysis 10 (3), 317-329, 2006 | 115 | 2006 |
| Adversarial image registration with application for MR and TRUS image fusion P Yan, S Xu, AR Rastinehad, BJ Wood Machine Learning in Medical Imaging: 9th International Workshop, MLMI 2018 …, 2018 | 114 | 2018 |
| Fast fit-free analysis of fluorescence lifetime imaging via deep learning JT Smith, R Yao, N Sinsuebphon, A Rudkouskaya, N Un, J Mazurkiewicz, ... Proceedings of the National Academy of Sciences 116 (48), 24019-24030, 2019 | 112 | 2019 |
Bradford J. WoodNational Institutes of HealthVerified email at nih.gov
