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 ...
To run the notebooks, you must first clone/download the official SAM2.1, MobileSAM, and TinySAM repositories from their respective sources, then place the provided script/ folders from this repo into ...
@article{chiaroni2025promi, title={ProMi: An Efficient Prototype-Mixture Baseline for Few-Shot Segmentation with Bounding-Box Annotations}, author={Chiaroni, Florent and Ayub, Ali and Ahmad, Ola}, ...
Results: This approach enabled the semantic representation of over 119,000 distinct data elements covering 13 billion instances. By extending the grammar, we successfully addressed critical ...
Objective: This study aims to explore patients’ experiences using the digital platform 1177-direkt for chat-based consultations in Swedish primary health care, with a focus on understanding their ...
Abstract: Medical image datasets often suffer from inadequate labeling, primarily due to ethical constraints, expertise challenges, and high annotation costs. In addition, domain shifts, resulting ...
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