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Yan-Jie Shi

Showing results (21-30 of 34) with videos related to

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Quantitative Imaging in Medicine and Surgery|December 18, 2023
CT radiomics in the identification of preoperative understaging in patients with clinical stage T1-2N0 esophageal squamous cell carcinomaBo Zhao, Shuo Yan, Zheng-Yan Jia, et al.
European Radiology|August 4, 2022
Quantitative CT evaluation after two cycles of induction chemotherapy to predict prognosis of patients with locally advanced oesophageal squamous cell carcinoma before undergoing definitive chemoradiotherapy/radiotherapyShuo Yan, Yan-Jie Shi, Chang Liu, et al.
BMC Cancer|October 14, 2025
Deep learning automatic segmentation and radiomics model for diagnosing pancreatic solid neoplasms in MRIYan-Jie Shi, Han Zhang, Lin-Lin Wang, et al.
Medicine|February 18, 2016
Spectral CT in the Demonstration of the Pancreatic Arteries and Their Branches: A Comparison With Conventional CTYan-Jie Shi, Xiao-Peng Zhang, Ying-Shi Sun, et al.
Physics and Imaging in Radiation Oncology|July 7, 2025
Rectal-RadioSAM: Large model-assisted multi-parametric magnetic resonance imaging pipeline for predicting response to neoadjuvant chemoradiotherapy in rectal cancer without human interventionShao-Jun Xia, Zhi-Nan Wang, Jia-Qi Wu, et al.
Frontiers in Oncology|September 25, 2020
Radiomics Analysis Based on Diffusion Kurtosis Imaging and T2 Weighted Imaging for Differentiation of Pancreatic Neuroendocrine Tumors From Solid Pseudopapillary TumorsYan-Jie Shi, Hai-Tao Zhu, Yu-Liang Liu, et al.
Radiology|April 22, 2020
Predicting Rectal Cancer Response to Neoadjuvant Chemoradiotherapy Using Deep Learning of Diffusion Kurtosis MRIXiao-Yan Zhang, Lin Wang, Hai-Tao Zhu, et al.
Journal of Cancer Research and Clinical Oncology|April 30, 2024
Dynamic change in the peritoneal cancer index based on CT after chemotherapy in the overall survival prediction of gastric cancer patients with peritoneal metastasisYi-Yuan Wei, Jie-Yuan Cai, Lin-Lin Wang, et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research|September 24, 2017
Radiomics Analysis for Evaluation of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal CancerZhenyu Liu, Xiao-Yan Zhang, Yan-Jie Shi, et al.
Radiotherapy and Oncology : Journal of the European Society for Therapeutic Radiology and Oncology|March 4, 2019
Quantitative analysis of diffusion weighted imaging to predict pathological good response to neoadjuvant chemoradiation for locally advanced rectal cancerZhenchao Tang, Xiao-Yan Zhang, Zhenyu Liu, et al.
Pageof 4

Showing results (21-30 of 34) with videos related to

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Pageof 4
Quantitative Imaging in Medicine and Surgery|December 18, 2023
CT radiomics in the identification of preoperative understaging in patients with clinical stage T1-2N0 esophageal squamous cell carcinomaBo Zhao, Shuo Yan, Zheng-Yan Jia, et al.
European Radiology|August 4, 2022
Quantitative CT evaluation after two cycles of induction chemotherapy to predict prognosis of patients with locally advanced oesophageal squamous cell carcinoma before undergoing definitive chemoradiotherapy/radiotherapyShuo Yan, Yan-Jie Shi, Chang Liu, et al.
BMC Cancer|October 14, 2025
Deep learning automatic segmentation and radiomics model for diagnosing pancreatic solid neoplasms in MRIYan-Jie Shi, Han Zhang, Lin-Lin Wang, et al.
Medicine|February 18, 2016
Spectral CT in the Demonstration of the Pancreatic Arteries and Their Branches: A Comparison With Conventional CTYan-Jie Shi, Xiao-Peng Zhang, Ying-Shi Sun, et al.
Physics and Imaging in Radiation Oncology|July 7, 2025
Rectal-RadioSAM: Large model-assisted multi-parametric magnetic resonance imaging pipeline for predicting response to neoadjuvant chemoradiotherapy in rectal cancer without human interventionShao-Jun Xia, Zhi-Nan Wang, Jia-Qi Wu, et al.
Frontiers in Oncology|September 25, 2020
Radiomics Analysis Based on Diffusion Kurtosis Imaging and T2 Weighted Imaging for Differentiation of Pancreatic Neuroendocrine Tumors From Solid Pseudopapillary TumorsYan-Jie Shi, Hai-Tao Zhu, Yu-Liang Liu, et al.
Radiology|April 22, 2020
Predicting Rectal Cancer Response to Neoadjuvant Chemoradiotherapy Using Deep Learning of Diffusion Kurtosis MRIXiao-Yan Zhang, Lin Wang, Hai-Tao Zhu, et al.
Journal of Cancer Research and Clinical Oncology|April 30, 2024
Dynamic change in the peritoneal cancer index based on CT after chemotherapy in the overall survival prediction of gastric cancer patients with peritoneal metastasisYi-Yuan Wei, Jie-Yuan Cai, Lin-Lin Wang, et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research|September 24, 2017
Radiomics Analysis for Evaluation of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal CancerZhenyu Liu, Xiao-Yan Zhang, Yan-Jie Shi, et al.
Radiotherapy and Oncology : Journal of the European Society for Therapeutic Radiology and Oncology|March 4, 2019
Quantitative analysis of diffusion weighted imaging to predict pathological good response to neoadjuvant chemoradiation for locally advanced rectal cancerZhenchao Tang, Xiao-Yan Zhang, Zhenyu Liu, et al.
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