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cs.CV2024

Decoupling Feature Representations of Ego and Other Modalities for Incomplete Multi-modal Brain Tumor Segmentation

Kaixiang Yang, Wenqi Shan, Xudong Li +6

Multi-modal brain tumor segmentation typically involves four magnetic resonance imaging (MRI) modalities, while incomplete modalities significantly degrade performance. Existing so…

cs.CV2024

Towards Synchronous Memorizability and Generalizability with Site-Modulated Diffusion Replay for Cross-Site Continual Segmentation

Dunyuan Xu, Xi Wang, Jingyang Zhang +1

The ability to learn sequentially from different data sites is crucial for a deep network in solving practical medical image diagnosis problems due to privacy restrictions and stor…

cs.CV2024

Test-time generative augmentation for medical image segmentation

Xiao Ma, Yuhui Tao, Zetian Zhang +7

Medical image segmentation is critical for clinical diagnosis, treatment planning, and monitoring, yet segmentation models often struggle with uncertainties stemming from occlusion…

cs.CV20241 cited

Multi-scale Spatio-temporal Transformer-based Imbalanced Longitudinal Learning for Glaucoma Forecasting from Irregular Time Series Images

Xikai Yang, Jian Wu, Xi Wang +3

Glaucoma is one of the major eye diseases that leads to progressive optic nerve fiber damage and irreversible blindness, afflicting millions of individuals. Glaucoma forecast is a…

cs.CV20244 cited

Cross-modality Guidance-aided Multi-modal Learning with Dual Attention for MRI Brain Tumor Grading

Dunyuan Xu, Xi Wang, Jinyue Cai +1

Brain tumor represents one of the most fatal cancers around the world, and is very common in children and the elderly. Accurate identification of the type and grade of tumor in the…