42 citations · 61 across the 3 of their papers we have counts for
5 papers
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…
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…
TransBTS: Multimodal Brain Tumor Segmentation Using Transformer
Wenxuan Wang, Chen Chen, Meng Ding +3
Transformer, which can benefit from global (long-range) information modeling using self-attention mechanisms, has been successful in natural language processing and 2D image classi…
3D Dilated Multi-Fiber Network for Real-time Brain Tumor Segmentation in MRI
Chen Chen, Xiaopeng Liu, Meng Ding +2
Brain tumor segmentation plays a pivotal role in medical image processing. In this work, we aim to segment brain MRI volumes. 3D convolution neural networks (CNN) such as 3D U-Net…