Detecting cardiovascular disease from mammograms with deep learning J Wang, H Ding, FA Bidgoli, B Zhou, C Iribarren, S Molloi, P Baldi IEEE transactions on medical imaging 36 (5), 1172-1181, 2017 | 246 | 2017 |
A multi-resolution approach for spinal metastasis detection using deep Siamese neural networks J Wang, Z Fang, N Lang, H Yuan, MY Su, P Baldi Computers in Biology and Medicine 84, 137-146, 2017 | 137 | 2017 |
A context-sensitive deep learning approach for microcalcification detection in mammograms J Wang, Y Yang Pattern Recognition 78, 12-22, 2018 | 94 | 2018 |
Simultaneous Diagnosis of Severity and Features of Diabetic Retinopathy in Fundus Photography Using Deep Learning J Wang, Y Bai, B Xia IEEE Journal of Biomedical and Health Informatics 24 (12), 3397-3407, 2020 | 67 | 2020 |
Improving SVM classifier with prior knowledge in microcalcification detection1 Y Yang, J Wang, Y Yang 2012 19th IEEE International Conference on Image Processing, 2837-2840, 2012 | 44 | 2012 |
A Simplified Cohen’s Kappa for Use in Binary Classification Data Annotation Tasks J Wang, Y Yang, B Xia IEEE Access 7, 164386-164397, 2019 | 35 | 2019 |
Global detection approach for clustered microcalcifications in mammograms using a deep learning network J Wang, RM Nishikawa, Y Yang Journal of Medical Imaging 4 (2), 024501-024501, 2017 | 33 | 2017 |
Bounding box tightness prior for weakly supervised image segmentation J Wang, B Xia Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 32 | 2021 |
Improving the accuracy in detection of clustered microcalcifications with a context-sensitive classification model J Wang, RM Nishikawa, Y Yang Medical Physics 43 (1), 159-170, 2016 | 27 | 2016 |
Feasibility of diagnosing both severity and features of diabetic retinopathy in fundus photography J Wang, Y Bai, B Xia IEEE Access 7, 102589-102597, 2019 | 26 | 2019 |
Exploiting rotation invariance with SVM classifier for microcalcification detection Y Yang, J Wang, Y Yang 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), 590-593, 2012 | 20 | 2012 |
Reduction of false positive detection in clustered microcalcifications J Wang, Y Yang, RM Nishikawa 2013 IEEE International Conference on Image Processing, 1433-1437, 2013 | 19 | 2013 |
Analysis of perceived similarity between pairs of microcalcification clusters in mammograms J Wang, H Jing, MN Wernick, RM Nishikawa, Y Yang Medical physics 41 (5), 051904, 2014 | 15 | 2014 |
Spatial density modeling for discirminating between benign and malignant microcalcification lesions J Wang, Y Yang 2013 IEEE 10th International Symposium on Biomedical Imaging, 133-136, 2013 | 11 | 2013 |
Relationships of Cohen's Kappa, Sensitivity, and Specificity for Unbiased Annotations J Wang, B Xia Proceedings of the 4th International Conference on Biomedical Signal and …, 2019 | 10 | 2019 |
Quantitative comparison of clustered microcalcifications in for‐presentation and for‐processing mammograms in full‐field digital mammography J Wang, RM Nishikawa, Y Yang Medical physics 44 (7), 3726-3738, 2017 | 10 | 2017 |
Tree-based multiscale pursuit J Wang, Q Wan, A Huang, T Gan 2009 International Conference on Communications, Circuits and Systems, 521-524, 2009 | 8 | 2009 |
A Hierarchical Learning Approach for Detection of Clustered Microcalcifications in Mammograms J Wang, Y Yang 2019 IEEE International Conference on Image Processing (ICIP), 804-808, 2019 | 7 | 2019 |
An image-retrieval aided diagnosis system for clustered microcalcifications J Wang, Y Yang, MN Wernick, RM Nishikawa 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 1076-1079, 2016 | 7 | 2016 |
Feature saliency analysis for perceptual similarity of clustered microcalcifications J Wang, Y Yang 2015 IEEE International Conference on Image Processing (ICIP), 775-778, 2015 | 6 | 2015 |