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Neuroimage
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May 23, 2023
msQSM: Morphology-based self-supervised deep learning for quantitative susceptibility mapping
Junjie He, Yunsong Peng, Bangkang Fu, et al.
Computer Methods and Programs in Biomedicine
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June 7, 2022
StoHisNet: A hybrid multi-classification model with CNN and Transformer for gastric pathology images
Bangkang Fu, Mudan Zhang, Junjie He, et al.
Computers in Biology and Medicine
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January 25, 2024
HmsU-Net: A hybrid multi-scale U-net based on a CNN and transformer for medical image segmentation
Bangkang Fu, Yunsong Peng, Junjie He, et al.
Computer Methods and Programs in Biomedicine
|
January 15, 2025
BMA-Net: A 3D bidirectional multi-scale feature aggregation network for prostate region segmentation
Bangkang Fu, Feng Liu, Junjie He, et al.
Neuroimage
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December 14, 2025
PI-uMSS: Prior information-based unsupervised magnetic source separation in quantitative susceptibility mapping
Junjie He, Bangkang Fu, Cen Pan, et al.
Computers in Biology and Medicine
|
December 22, 2023
SaB-Net: Self-attention backward network for gastric tumor segmentation in CT images
Junjie He, Mudan Zhang, Wuchao Li, et al.
Chinese Medical Journal
|
July 22, 2025
Integrating radiology and histology via co-attention deep learning for predicting progression-free survival in patients with metastatic prostate cancer
Yuanshen Zhao, Feng Liu, Chaofan Zhu, et al.
Medical Image Analysis
|
September 28, 2025
HSFSurv: A hybrid supervision framework at individual and feature levels for multimodal cancer survival analysis
Bangkang Fu, Junjie He, Xiaoli Zhang, et al.
Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society
|
September 18, 2025
Unveiling hidden risks: A Holistically-Driven Weak Supervision framework for ultra-short-term ACS prediction using CCTA
Zhen Liu, Bangkang Fu, Jiahui Mao, et al.
Computer Methods and Programs in Biomedicine
|
September 18, 2023
TGMIL: A hybrid multi-instance learning model based on the Transformer and the Graph Attention Network for whole-slide images classification of renal cell carcinoma
Xinhuan Sun, Wuchao Li, Bangkang Fu, et al.
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Search research articles
Search
Showing results (1-10 of 11) with videos related to
Sort By:
Page
of 2
Neuroimage
|
May 23, 2023
msQSM: Morphology-based self-supervised deep learning for quantitative susceptibility mapping
Junjie He, Yunsong Peng, Bangkang Fu, et al.
Computer Methods and Programs in Biomedicine
|
June 7, 2022
StoHisNet: A hybrid multi-classification model with CNN and Transformer for gastric pathology images
Bangkang Fu, Mudan Zhang, Junjie He, et al.
Computers in Biology and Medicine
|
January 25, 2024
HmsU-Net: A hybrid multi-scale U-net based on a CNN and transformer for medical image segmentation
Bangkang Fu, Yunsong Peng, Junjie He, et al.
Computer Methods and Programs in Biomedicine
|
January 15, 2025
BMA-Net: A 3D bidirectional multi-scale feature aggregation network for prostate region segmentation
Bangkang Fu, Feng Liu, Junjie He, et al.
Neuroimage
|
December 14, 2025
PI-uMSS: Prior information-based unsupervised magnetic source separation in quantitative susceptibility mapping
Junjie He, Bangkang Fu, Cen Pan, et al.
Computers in Biology and Medicine
|
December 22, 2023
SaB-Net: Self-attention backward network for gastric tumor segmentation in CT images
Junjie He, Mudan Zhang, Wuchao Li, et al.
Chinese Medical Journal
|
July 22, 2025
Integrating radiology and histology via co-attention deep learning for predicting progression-free survival in patients with metastatic prostate cancer
Yuanshen Zhao, Feng Liu, Chaofan Zhu, et al.
Medical Image Analysis
|
September 28, 2025
HSFSurv: A hybrid supervision framework at individual and feature levels for multimodal cancer survival analysis
Bangkang Fu, Junjie He, Xiaoli Zhang, et al.
Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society
|
September 18, 2025
Unveiling hidden risks: A Holistically-Driven Weak Supervision framework for ultra-short-term ACS prediction using CCTA
Zhen Liu, Bangkang Fu, Jiahui Mao, et al.
Computer Methods and Programs in Biomedicine
|
September 18, 2023
TGMIL: A hybrid multi-instance learning model based on the Transformer and the Graph Attention Network for whole-slide images classification of renal cell carcinoma
Xinhuan Sun, Wuchao Li, Bangkang Fu, et al.
Page
of 2