| Can peritumoral radiomics increase the efficiency of the prediction for lymph node metastasis in clinical stage T1 lung adenocarcinoma on CT? X Wang, X Zhao, Q Li, W Xia, Z Peng, R Zhang, Q Li, J Jian, W Wang, ... European radiology 29, 6049-6058, 2019 | 126 | 2019 |
| Deep learning–based fully automated detection and segmentation of lymph nodes on multiparametric-mri for rectal cancer: A multicentre study X Zhao, P Xie, M Wang, W Li, PJ Pickhardt, W Xia, F Xiong, R Zhang, ... EBioMedicine 56, 2020 | 61 | 2020 |
| MR image-based radiomics to differentiate type Ι and type ΙΙ epithelial ovarian cancers J Jian, Y Li, PJ Pickhardt, W Xia, Z He, R Zhang, S Zhao, X Zhao, S Cai, ... European Radiology 31, 403-410, 2021 | 54 | 2021 |
| Preoperative prediction of microvascular invasion in hepatocellular carcinoma: initial application of a radiomic algorithm based on grayscale ultrasound images Y Dong, L Zhou, W Xia, XY Zhao, Q Zhang, JM Jian, X Gao, WP Wang Frontiers in oncology 10, 353, 2020 | 53 | 2020 |
| Fully convolutional networks (FCNs)-based segmentation method for colorectal tumors on T2-weighted magnetic resonance images J Jian, F Xiong, W Xia, R Zhang, J Gu, X Wu, X Meng, X Gao Australasian physical & engineering sciences in medicine 41, 393-401, 2018 | 52 | 2018 |
| A cross-modal 3D deep learning for accurate lymph node metastasis prediction in clinical stage T1 lung adenocarcinoma X Zhao, X Wang, W Xia, Q Li, L Zhou, Q Li, R Zhang, J Cai, J Jian, L Fan, ... Lung Cancer 145, 10-17, 2020 | 49 | 2020 |
| MRI‐based machine learning for differentiating borderline from malignant epithelial ovarian tumors: A multicenter study Y Li, J Jian, PJ Pickhardt, F Ma, W Xia, H Li, R Zhang, S Zhao, S Cai, ... Journal of Magnetic Resonance Imaging 52 (3), 897-904, 2020 | 41 | 2020 |
| Deep learning predicts overall survival of patients with unresectable hepatocellular carcinoma treated by transarterial chemoembolization plus sorafenib L Zhang, W Xia, ZP Yan, JH Sun, BY Zhong, ZH Hou, MJ Yang, GH Zhou, ... Frontiers in Oncology 10, 593292, 2020 | 31 | 2020 |
| CT-based radiomics signatures can predict the tumor response of non-small cell lung cancer patients treated with first-line chemotherapy and targeted therapy F Yang, J Zhang, L Zhou, W Xia, R Zhang, H Wei, J Feng, X Zhao, J Jian, ... European Radiology, 1-10, 2022 | 23 | 2022 |
| Full convolutional network based multiple side‐output fusion architecture for the segmentation of rectal tumors in magnetic resonance images: a multi‐vendor study M Wang, P Xie, Z Ran, J Jian, R Zhang, W Xia, T Yu, C Ni, J Gu, X Gao, ... Medical physics 46 (6), 2659-2668, 2019 | 21 | 2019 |
| Multiple instance convolutional neural network with modality-based attention and contextual multi-instance learning pooling layer for effective differentiation between … J Jian, W Xia, R Zhang, X Zhao, J Zhang, X Wu, J Qiang, X Gao Artificial intelligence in medicine 121, 102194, 2021 | 19 | 2021 |
| MRI‐Based Multiple Instance Convolutional Neural Network for Increased Accuracy in the Differentiation of Borderline and Malignant Epithelial Ovarian Tumors J Jian, Y Li, W Xia, Z He, R Zhang, H Li, X Zhao, S Zhao, J Zhang, S Cai, ... Journal of Magnetic Resonance Imaging 56 (1), 173-181, 2022 | 13 | 2022 |
| Deep learning-based segmentation of epithelial ovarian cancer on T2-weighted magnetic resonance images D Hu, J Jian, Y Li, X Gao Quantitative Imaging in Medicine and Surgery 13 (3), 1464, 2023 | 11 | 2023 |
| 3D multi-scale, multi-task, and multi-label deep learning for prediction of lymph node metastasis in T1 lung adenocarcinoma patients' CT images X Zhao, X Wang, W Xia, R Zhang, J Jian, J Zhang, Y Zhu, Y Tang, Z Li, ... Computerized Medical Imaging and Graphics 93, 101987, 2021 | 11 | 2021 |
| Preoperative CECT-based Radiomic signature for Predicting the response of Transarterial Chemoembolization (TACE) therapy in Hepatocellular Carcinoma H Bai, S Meng, C Xiong, Z Liu, W Shi, Q Ren, W Xia, XY Zhao, J Jian, ... CardioVascular and Interventional Radiology 45 (10), 1524-1533, 2022 | 8 | 2022 |
| Deep learning-based fully automated diagnosis of melanocytic lesions by using whole slide images Y Bao, J Zhang, X Zhao, H Zhou, Y Chen, J Jian, T Shi, X Gao Journal of Dermatological Treatment 33 (5), 2571-2577, 2022 | 5 | 2022 |
| MRI texture analysis for preoperative prediction of lymph node metastasis in patients with nonsquamous cell cervical carcinoma ML Xiao, Y Wei, J Zhang, JM Jian, Y Song, ZJ Lin, L Qian, GF Zhang, ... Academic Radiology 29 (11), 1661-1671, 2022 | 4 | 2022 |
| Deep learning-based fully automated segmentation of regional muscle volume and spatial intermuscular fat using CT R Zhang, A He, W Xia, Y Su, J Jian, Y Liu, Z Guo, W Shi, Z Zhang, B He, ... Academic Radiology 30 (10), 2280-2289, 2023 | 2 | 2023 |
| Contribution of whole slide imaging‐based deep learning in the assessment of intraoperative and postoperative sections in neuropathology L Shi, L Shen, J Jian, W Xia, KD Yang, Y Tian, J Huang, B Yuan, L Shen, ... Brain Pathology 33 (4), e13160, 2023 | 2 | 2023 |
| Peritumoral MRI radiomics features increase the evaluation efficiency for response to chemotherapy in patients with epithelial ovarian cancer Y Li, J Jian, H Ge, X Gao, J Qiang Journal of Magnetic Resonance Imaging, 2024 | 1 | 2024 |
Wei XiaSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of SciencesVerified email at sibet.ac.cn
