6 papers
CoPA: Hierarchical Concept Prompting and Aggregating Network for Explainable Diagnosis
Yiheng Dong, Yi Lin, Xin Yang
The transparency of deep learning models is essential for clinical diagnostics. Concept Bottleneck Model provides clear decision-making processes for diagnosis by transforming the…
LLM-driven Medical Report Generation via Communication-efficient Heterogeneous Federated Learning
Haoxuan Che, Haibo Jin, Zhengrui Guo +3
LLMs have demonstrated significant potential in Medical Report Generation (MRG), yet their development requires large amounts of medical image-report pairs, which are commonly scat…
Boosting Convolution with Efficient MLP-Permutation for Volumetric Medical Image Segmentation
Yi Lin, Xiao Fang, Dong Zhang +2
Recently, the advent of vision Transformer (ViT) has brought substantial advancements in 3D dataset benchmarks, particularly in 3D volumetric medical image segmentation (Vol-MedSeg…
Label-Efficient Deep Learning in Medical Image Analysis: Challenges and Future Directions
Cheng Jin, Zhengrui Guo, Yi Lin +2
Deep learning has significantly advanced medical imaging analysis (MIA), achieving state-of-the-art performance across diverse clinical tasks. However, its success largely depends…
Rethinking Boundary Detection in Deep Learning-Based Medical Image Segmentation
Yi Lin, Dong Zhang, Xiao Fang +3
Medical image segmentation is a pivotal task within the realms of medical image analysis and computer vision. While current methods have shown promise in accurately segmenting majo…
Merging Context Clustering with Visual State Space Models for Medical Image Segmentation
Yun Zhu, Dong Zhang, Yi Lin +2
Medical image segmentation demands the aggregation of global and local feature representations, posing a challenge for current methodologies in handling both long-range and short-r…