123 citations · 232 across the 10 of their papers we have counts for
6 papers · 1 filter
MF2-MVQA: A Multi-stage Feature Fusion method for Medical Visual Question Answering
Shanshan Song, Jiangyun Li, Jing Wang +2
There is a key problem in the medical visual question answering task that how to effectively realize the feature fusion of language and medical images with limited datasets. In ord…
Med-DANet: Dynamic Architecture Network for Efficient Medical Volumetric Segmentation
Wenxuan Wang, Chen Chen, Jing Wang +3
For 3D medical image (e.g. CT and MRI) segmentation, the difficulty of segmenting each slice in a clinical case varies greatly. Previous research on volumetric medical image segmen…
Positive-Negative Equal Contrastive Loss for Semantic Segmentation
Jing Wang, Jiangyun Li, Wei Li +3
The contextual information is critical for various computer vision tasks, previous works commonly design plug-and-play modules and structural losses to effectively extract and aggr…
Attention guided global enhancement and local refinement network for semantic segmentation
Jiangyun Li, Sen Zha, Chen Chen +3
The encoder-decoder architecture is widely used as a lightweight semantic segmentation network. However, it struggles with a limited performance compared to a well-designed Dilated…
Category Guided Attention Network for Brain Tumor Segmentation in MRI
Jiangyun Li, Hong Yu, Chen Chen +2
Objective: Magnetic resonance imaging (MRI) has been widely used for the analysis and diagnosis of brain diseases. Accurate and automatic brain tumor segmentation is of paramount i…
TransBTSV2: Towards Better and More Efficient Volumetric Segmentation of Medical Images
Jiangyun Li, Wenxuan Wang, Chen Chen +4
Transformer, benefiting from global (long-range) information modeling using self-attention mechanism, has been successful in natural language processing and computer vision recentl…