| Identifying EGFR mutations in lung adenocarcinoma by noninvasive imaging using radiomics features and random forest modeling TY Jia, JF Xiong, XY Li, W Yu, ZY Xu, XW Cai, JC Ma, YC Ren, R Larsson, ... European radiology 29, 4742-4750, 2019 | 139 | 2019 |
| Automatic lung nodule classification with radiomics approach J Ma, Q Wang, Y Ren, H Hu, J Zhao Medical Imaging 2016: PACS and Imaging Informatics: Next Generation and …, 2016 | 60 | 2016 |
| The role of PET-based radiomic features in predicting local control of esophageal cancer treated with concurrent chemoradiotherapy J Xiong, W Yu, J Ma, Y Ren, X Fu, J Zhao Scientific Reports 8 (1), 9902, 2018 | 41 | 2018 |
| Automatic detection of lung nodules: false positive reduction using convolution neural networks and handcrafted features L Fu, J Ma, Y Ren, YS Han, J Zhao Medical Imaging 2017: Computer-Aided Diagnosis 10134, 60-67, 2017 | 39 | 2017 |
| Computerized detection of lung nodules through radiomics J Ma, Z Zhou, Y Ren, J Xiong, L Fu, Q Wang, J Zhao Medical physics 44 (8), 4148-4158, 2017 | 34 | 2017 |
| Improved false positive reduction by novel morphological features for computer-aided polyp detection in CT colonography Y Ren, J Ma, J Xiong, Y Chen, L Lu, J Zhao IEEE journal of biomedical and health informatics 23 (1), 324-333, 2018 | 19 | 2018 |
| Automated identification of optimal portal venous phase timing with convolutional neural networks J Ma, L Dercle, P Lichtenstein, D Wang, A Chen, J Zhu, H Piessevaux, ... Academic radiology 27 (2), e10-e18, 2020 | 17 | 2020 |
| Automatic detection of lung nodules using 3D deep convolutional neural networks L Fu, J Ma, Y Chen, R Larsson, J Zhao Journal of Shanghai Jiaotong University (Science) 24, 517-523, 2019 | 16 | 2019 |
| Using a single abdominal computed tomography image to differentiate five contrast-enhancement phases: A machine-learning algorithm for radiomics-based precision medicine L Dercle, J Ma, C Xie, A Chen, D Wang, L Luk, P Revel-Mouroz, P Otal, ... European journal of radiology 125, 108850, 2020 | 15 | 2020 |
| High-performance CAD-CTC scheme using shape index, multiscale enhancement filters, and radiomic features Y Ren, J Ma, J Xiong, L Lu, J Zhao IEEE Transactions on Biomedical Engineering 64 (8), 1924-1934, 2016 | 13 | 2016 |
| Optimization‐based scatter estimation using primary modulation for computed tomography Y Chen, Y Song, J Ma, J Zhao Medical Physics 43 (8Part1), 4753-4767, 2016 | 13 | 2016 |
| Distinguishing benign and malignant lesions on contrast-enhanced breast cone-beam CT with deep learning neural architecture search J Ma, N He, JH Yoon, R Ha, J Li, W Ma, T Meng, L Lu, LH Schwartz, Y Wu, ... European Journal of Radiology 142, 109878, 2021 | 10 | 2021 |
| Lung field segmentation using weighted sparse shape composition with robust initialization J Xiong, Y Shao, J Ma, Y Ren, Q Wang, J Zhao Medical physics 44 (11), 5916-5929, 2017 | 8 | 2017 |
| Limited-range few-view CT: using historical images for ROI reconstruction in solitary lung nodules follow-up examination W Zhang, Y Song, Y Chen, J Ma, J Sun, J Zhao IEEE Transactions on Medical Imaging 36 (12), 2569-2577, 2017 | 5 | 2017 |
| PUNDIT: Pulmonary nodule detection with image category transformation W Zhao, J Ma, L Zhao, R Hou, L Qiu, X Fu, J Zhao Medical Physics 50 (5), 2914-2927, 2023 | 3 | 2023 |
| Deep learning-based covert brain infarct detection from multiple MRI sequences S Zhao, HF Bagce, V Spektor, Y Chou, G Gao, CD Morales, H Yang, J Ma, ... Neurocomputing 550, 126464, 2023 | 1 | 2023 |
| Machine learning-based identification of contrast-enhancement phase of computed tomography scans S Guha, A Ibrahim, Q Wu, P Geng, Y Chou, H Yang, J Ma, L Lu, D Wang, ... Plos one 19 (2), e0294581, 2024 | | 2024 |
| Optimization-based scatter estimation using semi-transparent beam absorber array Y Chen, Y Song, J Ma, J Zhao 2015 37th Annual International Conference of the IEEE Engineering in …, 2015 | | 2015 |
Jun ZhaoProfessor of Biomedical Engineering, Shanghai Jiao Tong UniversityVerified email at sjtu.edu.cn
