research
∙
09/12/2023
Enhancing Representation in Radiography-Reports Foundation Model: A Granular Alignment Algorithm Using Masked Contrastive Learning
Recently, multi-modal vision-language foundation models have gained sign...
share
research
∙
04/12/2023
Few-shot Class-incremental Learning for Cross-domain Disease Classification
The ability to incrementally learn new classes from limited samples is c...
research
∙
11/16/2022
Semi-Supervised and Self-Supervised Collaborative Learning for Prostate 3D MR Image Segmentation
Volumetric magnetic resonance (MR) image segmentation plays an important...
research
∙
11/16/2022
Uncertainty-Aware Multi-Parametric Magnetic Resonance Image Information Fusion for 3D Object Segmentation
Multi-parametric magnetic resonance (MR) imaging is an indispensable too...
research
∙
11/15/2022
DIGEST: Deeply supervIsed knowledGE tranSfer neTwork learning for brain tumor segmentation with incomplete multi-modal MRI scans
Brain tumor segmentation based on multi-modal magnetic resonance imaging...
research
∙
11/15/2022
Adaptive PromptNet For Auxiliary Glioma Diagnosis without Contrast-Enhanced MRI
Multi-contrast magnetic resonance imaging (MRI)-based automatic auxiliar...
research
∙
03/18/2022
Rethinking the optimization process for self-supervised model-driven MRI reconstruction
Recovering high-quality images from undersampled measurements is critica...
research
∙
08/05/2020
A coarse-to-fine framework for unsupervised multi-contrast MR image deformable registration with dual consistency constraint
Multi-contrast magnetic resonance (MR) image registration is essential i...
research
∙
08/14/2019
D-UNet: a dimension-fusion U shape network for chronic stroke lesion segmentation
Assessing the location and extent of lesions caused by chronic stroke is...
research
∙
07/16/2019
