| Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology images J Xu, L Xiang, Q Liu, H Gilmore, J Wu, J Tang, A Madabhushi IEEE Transactions on Medical Imaging 35 (1), 119-130, 2016 | 930 | 2016 |
| Computer-aided detection and diagnosis of breast cancer with mammography: recent advances J Tang, RM Rangayyan, J Xu, I El Naqa, Y Yang IEEE transactions on information technology in biomedicine 13 (2), 236-251, 2009 | 813 | 2009 |
| A Deep Convolutional Neural Network for Segmenting and Classifying Epithelial and Stromal Regions in Histopathological Images J Xu, X Luo, G Wang, H Gilmore, A Madabhushi Neurocomputing, 2016 | 513 | 2016 |
| Expectation–maximization-driven geodesic active contour with overlap resolution (emagacor): Application to lymphocyte segmentation on breast cancer histopathology H Fatakdawala, J Xu, A Basavanhally, G Bhanot, S Ganesan, M Feldman, ... IEEE Transactions on Biomedical Engineering 57 (7), 1676-1689, 2010 | 250 | 2010 |
| Stacked Sparse Autoencoder (SSAE) based Framework for Nuclei Patch Classification on Breast Cancer Histopathology J Xu, L Xiang, R Hang, J Wu 2014 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2014 | 97 | 2014 |
| Fusing heterogeneous features from stacked sparse autoencoder for histopathological image analysis X Zhang, H Dou, T Ju, J Xu, S Zhang IEEE journal of biomedical and health informatics 20 (5), 1377-1383, 2015 | 89 | 2015 |
| Incorporating domain knowledge for tubule detection in breast histopathology using O'Callaghan neighborhoods A Basavanhally, E Yu, J Xu, S Ganesan, M Feldman, J Tomaszewski, ... Medical imaging 2011: Computer-aided diagnosis 7963, 305-319, 2011 | 75 | 2011 |
| Computer-aided prognosis on breast cancer with hematoxylin and eosin histopathology images: A review JM Chen, Y Li, J Xu, L Gong, LW Wang, WL Liu, J Liu Tumor Biology 39 (3), 1010428317694550, 2017 | 71 | 2017 |
| Accelerated two-stage particle swarm optimization for clustering not-well-separated data X Xu, J Li, MC Zhou, J Xu, J Cao IEEE Transactions on Systems, Man, and Cybernetics: Systems 50 (11), 4212-4223, 2018 | 70 | 2018 |
| A high-throughput active contour scheme for segmentation of histopathological imagery J Xu, A Janowczyk, S Chandran, A Madabhushi Medical image analysis 15 (6), 851-862, 2011 | 65 | 2011 |
| Sparse Non-negative Matrix Factorization (SNMF) based Color Unmixing for Breast Histopathological Image Analysis J Xu, L Xiang, G Wang, S Ganesan, M Feldman, N NC Shih, H Gilmore, ... Computerized Medical Imaging and Graphics 46, 20-29, 2015 | 63 | 2015 |
| A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study C Lu, K Bera, X Wang, P Prasanna, J Xu, A Janowczyk, N Beig, M Yang, ... The Lancet Digital Health 2 (11), e594-e606, 2020 | 46 | 2020 |
| A weighted mean shift, normalized cuts initialized color gradient based geodesic active contour model: applications to histopathology image segmentation J Xu, A Janowczyk, S Chandran, A Madabhushi Medical imaging 2010: Image processing 7623, 325-336, 2010 | 46 | 2010 |
| Deep learning for histopathological image analysis: Towards computerized diagnosis on cancers J Xu, C Zhou, B Lang, Q Liu Deep learning and convolutional neural networks for medical image computing …, 2017 | 42 | 2017 |
| Computer-aided prognosis of ER+ breast cancer histopathology and correlating survival outcome with oncotype DX assay A Basavanhally, J Xu, A Madabhushi, S Ganesan 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro …, 2009 | 41 | 2009 |
| Multi-pass adaptive voting for nuclei detection in histopathological images C Lu, H Xu, J Xu, H Gilmore, M Mandal, A Madabhushi Scientific reports 6 (1), 33985, 2016 | 37 | 2016 |
| Absolute exponential stability of recurrent neural networks with generalized activation function J Xu, YY Cao, Y Sun, J Tang IEEE transactions on neural networks 19 (6), 1075-1089, 2008 | 34 | 2008 |
| Markov random field driven region-based active contour model (MaRACel): application to medical image segmentation J Xu, JP Monaco, A Madabhushi Medical Image Computing and Computer-Assisted Intervention–MICCAI 2010: 13th …, 2010 | 32 | 2010 |
| CT-radiomic approach to predict G1/2 nonfunctional pancreatic neuroendocrine tumor Z Zhao, Y Bian, H Jiang, X Fang, J Li, K Cao, C Ma, L Wang, J Zheng, ... Academic Radiology 27 (12), e272-e281, 2020 | 31 | 2020 |
| Spectral embedding based active contour (SEAC) for lesion segmentation on breast dynamic contrast enhanced magnetic resonance imaging SC Agner, J Xu, A Madabhushi Medical physics 40 (3), 032305, 2013 | 31 | 2013 |
Anant MadabhushiDepartment of Biomedical Engineering, Professor, Biomedical Engineering, Emory Univ & Georgia TechGeverifieerd e-mailadres voor emory.edu
