| Bayesian parameter estimation and segmentation in the multi-atlas random orbit model X Tang, K Oishi, AV Faria, AE Hillis, MS Albert, S Mori, MI Miller PloS one 8 (6), e65591, 2013 | 182 | 2013 |
| Shape abnormalities of subcortical and ventricular structures in mild cognitive impairment and Alzheimer's disease: detecting, quantifying, and predicting X Tang, D Holland, AM Dale, L Younes, MI Miller, ... Human brain mapping 35 (8), 3701-3725, 2014 | 165 | 2014 |
| Automated anatomical labeling by multi-contrast diffeomorphic probability fusion MI Miller, S Mori, X Tang US Patent 10,535,133, 2020 | 89 | 2020 |
| A deep learning framework for pancreas segmentation with multi-atlas registration and 3D level-set Y Zhang, J Wu, Y Liu, Y Chen, W Chen, EX Wu, C Li, X Tang Medical Image Analysis 68, 101884, 2021 | 87 | 2021 |
| The diffeomorphometry of regional shape change rates and its relevance to cognitive deterioration in mild cognitive impairment and A lzheimer's disease X Tang, D Holland, AM Dale, L Younes, MI Miller, ... Human brain mapping 36 (6), 2093-2117, 2015 | 76 | 2015 |
| MI-UNet: multi-inputs UNet incorporating brain parcellation for stroke lesion segmentation from T1-weighted magnetic resonance images Y Zhang, J Wu, Y Liu, Y Chen, EX Wu, X Tang IEEE Journal of Biomedical and Health Informatics 25 (2), 526-535, 2020 | 71 | 2020 |
| Shape and diffusion tensor imaging based integrative analysis of the hippocampus and the amygdala in Alzheimer's disease X Tang, Y Qin, J Wu, M Zhang, W Zhu, MI Miller Magnetic resonance imaging 34 (8), 1087-1099, 2016 | 68 | 2016 |
| Tools for multiple granularity analysis of brain MRI data for individualized image analysis A Djamanakova, X Tang, X Li, AV Faria, C Ceritoglu, K Oishi, AE Hillis, ... Neuroimage 101, 168-176, 2014 | 65 | 2014 |
| Multi-contrast multi-atlas parcellation of diffusion tensor imaging of the human brain X Tang, S Yoshida, J Hsu, TAGM Huisman, AV Faria, K Oishi, K Kutten, ... PloS one 9 (5), e96985, 2014 | 65 | 2014 |
| Segmentation of brain magnetic resonance images based on multi-atlas likelihood fusion: testing using data with a broad range of anatomical and photometric profiles X Tang, D Crocetti, K Kutten, C Ceritoglu, MS Albert, S Mori, SH Mostofsky, ... Frontiers in neuroscience 9, 61, 2015 | 64 | 2015 |
| Skip connection U-Net for white matter hyperintensities segmentation from MRI J Wu, Y Zhang, K Wang, X Tang IEEE Access 7, 155194-155202, 2019 | 61 | 2019 |
| Prostate segmentation using 2D bridged U-net W Chen, Y Zhang, J He, Y Qiao, Y Chen, H Shi, EX Wu, X Tang 2019 International Joint Conference on Neural Networks (IJCNN), 1-7, 2019 | 61 | 2019 |
| Regional morphometric abnormalities and clinical relevance in Wilson's disease L Zou, Y Song, X Zhou, J Chu, X Tang Movement disorders 34 (4), 545-554, 2019 | 59 | 2019 |
| Computational analysis of LDDMM for brain mapping C Ceritoglu, X Tang, M Chow, D Hadjiabadi, D Shah, T Brown, ... Frontiers in neuroscience 7, 151, 2013 | 59 | 2013 |
| Hippocampal sub‐regional shape and physical activity in older adults VR Varma, X Tang, MC Carlson Hippocampus 26 (8), 1051-1060, 2016 | 58 | 2016 |
| Gamma challenge: glaucoma grading from multi-modality images J Wu, H Fang, F Li, H Fu, F Lin, J Li, Y Huang, Q Yu, S Song, X Xu, Y Xu, ... Medical Image Analysis 90, 102938, 2023 | 53 | 2023 |
| Deep learning initialized and gradient enhanced level-set based segmentation for liver tumor from CT images Y Zhang, B Jiang, J Wu, D Ji, Y Liu, Y Chen, EX Wu, X Tang IEEE Access 8, 76056-76068, 2020 | 52 | 2020 |
| APOE affects the volume and shape of the amygdala and the hippocampus in mild cognitive impairment and Alzheimer’s disease: age matters X Tang, D Holland, AM Dale, MI Miller, ... Journal of Alzheimer's Disease 47 (3), 645-660, 2015 | 51 | 2015 |
| Baseline shape diffeomorphometry patterns of subcortical and ventricular structures in predicting conversion of mild cognitive impairment to Alzheimer's disease X Tang, D Holland, AM Dale, L Younes, MI Miller, ... Journal of Alzheimer's Disease 44 (2), 599-611, 2015 | 50 | 2015 |
| Bsda-net: A boundary shape and distance aware joint learning framework for segmenting and classifying octa images L Lin, Z Wang, J Wu, Y Huang, J Lyu, P Cheng, J Wu, X Tang Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 47 | 2021 |
Michael I. MillerProfessor and Director of Biomedical Engineering, Johns Hopkins UniversityVerified email at jhu.edu
