Abstract: Deep learning models for medical image segmentation often struggle with task-specific characteristics, limiting their generalization to unseen tasks with new anatomies, labels, or modalities ...
Abstract: In this paper, we present UISE, a unified image segmentation framework that achieves efficient performance across various segmentation tasks, eliminating the need for multiple specialized ...
State Space Models (SSMs) are emerging as a practical alternative to transformers, offering similar or better performance with significantly fewer parameters and lower compute requirements. Mamba, the ...
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