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Pinggui Lei

Showing results (31-40 of 57) with videos related to

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Journal of X-Ray Science and Technology|June 23, 2020
Differentiating pneumonia with and without COVID-19 using chest CT images: from qualitative to quantitativeZicong Li, Bingliang Zeng, Pinggui Lei, et al.
European Journal of Radiology|November 18, 2024
Assessment and integration of multiparametric MRI for liver fibrosis staging in rat non-alcoholic steatohepatitis: Evaluation of diagnostic efficiency and model interpretationZhaoshu Huang, Xing Xia, Yao Liang, et al.
Medicine|March 3, 2021
Retroperitoneal dendritic cell sarcoma: A case reportChuanhong Wang, Pinggui Lei, Yong Wan, et al.
Journal of X-Ray Science and Technology|June 10, 2026
Development and evaluation of deep learning models for automatic coronary stenosis segmentation in X-ray angiographyManli Zhang, Fangyan Li, Haijun Guo, et al.
Academic Radiology|May 19, 2020
Value of MRI Radiomics Based on Enhanced T1WI Images in Prediction of Meningiomas GradeHairui Chu, Xiaoqi Lin, Jian He, et al.
Academic Radiology|June 27, 2025
MRI-Based Radiomic Biomarkers for Non-invasive Assessment of Liver Fibrosis in MASLD: Diagnostic Performance and Molecular Mechanisms in a Rat ModelFangyan Li, Yao Liang, Xing Xia, et al.
Scientific Reports|August 30, 2024
A combination model of CT-based radiomics and clinical biomarkers for staging liver fibrosis in the patients with chronic liver diseaseMaowen Tang, Yuhui Wu, Na Hu, et al.
Journal of X-Ray Science and Technology|July 1, 2019
NAFLD evaluation: Which is more appropriate, multislice computed tomography or ultrasound real-time shear wave elastography?Pinggui Lei, Jun Jiao, Hong Li, et al.
Abdominal Radiology (New York)|June 4, 2026
Differentiating advanced from non-advanced hepatic fibrosis: a hybrid deep learning-radiomics model leveraging synthetic contrast-enhanced CT from CycleGANJian He, Yue Pan, Menghua Yang, et al.
European Radiology Experimental|November 20, 2023
CT-based methods for assessment of metabolic dysfunction associated with fatty liver diseaseNa Hu, Gang Yan, Maowen Tang, et al.
Pageof 6

Showing results (31-40 of 57) with videos related to

Sort By:
Pageof 6
Journal of X-Ray Science and Technology|June 23, 2020
Differentiating pneumonia with and without COVID-19 using chest CT images: from qualitative to quantitativeZicong Li, Bingliang Zeng, Pinggui Lei, et al.
European Journal of Radiology|November 18, 2024
Assessment and integration of multiparametric MRI for liver fibrosis staging in rat non-alcoholic steatohepatitis: Evaluation of diagnostic efficiency and model interpretationZhaoshu Huang, Xing Xia, Yao Liang, et al.
Medicine|March 3, 2021
Retroperitoneal dendritic cell sarcoma: A case reportChuanhong Wang, Pinggui Lei, Yong Wan, et al.
Journal of X-Ray Science and Technology|June 10, 2026
Development and evaluation of deep learning models for automatic coronary stenosis segmentation in X-ray angiographyManli Zhang, Fangyan Li, Haijun Guo, et al.
Academic Radiology|May 19, 2020
Value of MRI Radiomics Based on Enhanced T1WI Images in Prediction of Meningiomas GradeHairui Chu, Xiaoqi Lin, Jian He, et al.
Academic Radiology|June 27, 2025
MRI-Based Radiomic Biomarkers for Non-invasive Assessment of Liver Fibrosis in MASLD: Diagnostic Performance and Molecular Mechanisms in a Rat ModelFangyan Li, Yao Liang, Xing Xia, et al.
Scientific Reports|August 30, 2024
A combination model of CT-based radiomics and clinical biomarkers for staging liver fibrosis in the patients with chronic liver diseaseMaowen Tang, Yuhui Wu, Na Hu, et al.
Journal of X-Ray Science and Technology|July 1, 2019
NAFLD evaluation: Which is more appropriate, multislice computed tomography or ultrasound real-time shear wave elastography?Pinggui Lei, Jun Jiao, Hong Li, et al.
Abdominal Radiology (New York)|June 4, 2026
Differentiating advanced from non-advanced hepatic fibrosis: a hybrid deep learning-radiomics model leveraging synthetic contrast-enhanced CT from CycleGANJian He, Yue Pan, Menghua Yang, et al.
European Radiology Experimental|November 20, 2023
CT-based methods for assessment of metabolic dysfunction associated with fatty liver diseaseNa Hu, Gang Yan, Maowen Tang, et al.
Pageof 6