105 citations · 297 across the 52 of their papers we have counts for
14 papers · 1 filter
Joint Imaging-ROI Representation Learning via Cross-View Contrastive Alignment for Brain Disorder Classification
Wei Liang, Lifang He
Brain imaging classification is commonly approached from two perspectives: modeling the full image volume to capture global anatomical context, or constructing ROI-based graphs to…
Adaptive Clinical-Aware Latent Diffusion for Multimodal Brain Image Generation and Missing Modality Imputation
Rong Zhou, Houliang Zhou, Yao Su +4
Multimodal neuroimaging provides complementary insights for Alzheimer's disease diagnosis, yet clinical datasets frequently suffer from missing modalities. We propose ACADiff, a fr…
SAMed-2: Selective Memory Enhanced Medical Segment Anything Model
Zhiling Yan, Sifan Song, Dingjie Song +11
Recent "segment anything" efforts show promise by learning from large-scale data, but adapting such models directly to medical images remains challenging due to the complexity of m…
Towards a general-purpose foundation model for fMRI analysis
Cheng Wang, Yu Jiang, Zhihao Peng +18
Functional MRI (fMRI) is crucial for studying brain function and diagnosing neurological disorders. However, existing analysis methods suffer from reproducibility and transferabili…
Biomedical SAM 2: Segment Anything in Biomedical Images and Videos
Zhiling Yan, Weixiang Sun, Rong Zhou +8
Medical image segmentation and video object segmentation are essential for diagnosing and analyzing diseases by identifying and measuring biological structures. Recent advances in…
Bora: Biomedical Generalist Video Generation Model
Weixiang Sun, Xiaocao You, Ruizhe Zheng +5
Generative models hold promise for revolutionizing medical education, robot-assisted surgery, and data augmentation for medical AI development. Diffusion models can now generate re…