Rongpin Wang
Orcid: 0000-0001-7587-4181
According to our database1,
Rongpin Wang
authored at least 26 papers
between 2019 and 2024.
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Bibliography
2024
HmsU-Net: A hybrid multi-scale U-net based on a CNN and transformer for medical image segmentation.
Comput. Biol. Medicine, March, 2024
SaB-Net: Self-attention backward network for gastric tumor segmentation in CT images.
Comput. Biol. Medicine, February, 2024
A nutrition-based radiomics-clinical model to predict the prognosis of patients with acute-on-chronic liver failure.
Displays, 2024
Identifying pathological groups from MRI in prostate cancer using graph representation learning.
Displays, 2024
A hybrid classification model with radiomics and CNN for high and low grading of prostate cancer Gleason score on mp-MRI.
Displays, 2024
3D convolutional network with edge detection for prostate gland and tumor segmentation on T2WI and ADC.
Biomed. Signal Process. Control., 2024
mQSM: Multitask Learning-Based Quantitative Susceptibility Mapping for Iron Analysis in Brain.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
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.
Comput. Methods Programs Biomed., December, 2023
A radiomics based approach using adrenal gland and periadrenal fat CT images to allocate COVID-19 health care resources fairly.
BMC Medical Imaging, December, 2023
Deep wavelet scattering orthogonal fusion network for glioma IDH mutation status prediction.
Comput. Biol. Medicine, November, 2023
A robust and efficient AI assistant for breast tumor segmentation from DCE-MRI via a spatial-temporal framework.
Patterns, September, 2023
msQSM: Morphology-based self-supervised deep learning for quantitative susceptibility mapping.
NeuroImage, 2023
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
2022
StoHisNet: A hybrid multi-classification model with CNN and Transformer for gastric pathology images.
Comput. Methods Programs Biomed., 2022
2021
A Coarse-to-Fine Deformable Transformation Framework for Unsupervised Multi-Contrast MR Image Registration with Dual Consistency Constraint.
IEEE Trans. Medical Imaging, 2021
Multi-Focus Network to Decode Imaging Phenotype for Overall Survival Prediction of Gastric Cancer Patients.
IEEE J. Biomed. Health Informatics, 2021
2D and 3D CT Radiomic Features Performance Comparison in Characterization of Gastric Cancer: A Multi-Center Study.
IEEE J. Biomed. Health Informatics, 2021
Learning a Deep CNN Denoising Approach Using Anatomical Prior Information Implemented With Attention Mechanism for Low-Dose CT Imaging on Clinical Patient Data From Multiple Anatomical Sites.
IEEE J. Biomed. Health Informatics, 2021
Toward human intervention-free clinical diagnosis of intracranial aneurysm via deep neural network.
Patterns, 2021
Considering anatomical prior information for low-dose CT image enhancement using attribute-augmented Wasserstein generative adversarial networks.
Neurocomputing, 2021
An AI-based radiomics nomogram for disease prognosis in patients with COVID-19 pneumonia using initial CT images and clinical indicators.
Int. J. Medical Informatics, 2021
FaNet: fast assessment network for the novel coronavirus (COVID-19) pneumonia based on 3D CT imaging and clinical symptoms.
Appl. Intell., 2021
2020
Patterns, 2020
CoRR, 2020
A coarse-to-fine framework for unsupervised multi-contrast MR image deformable registration with dual consistency constraint.
CoRR, 2020
2019
IEEE Access, 2019