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September 10, 2025IEEE Journal of Biomedical and Health Informatics

Leveraging Multi-Text Joint Prompts in SAM for Robust Medical Image Segmentation

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Authors

XZXu ZhangHZHuangxuan ZhaoLZLefei Zhang

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Overview

This framework improves image segmentation using text prompts, indicating better performance than traditional methods.

Key Points

  • The proposed framework enhances medical image segmentation through multi-text prompts, improving efficiency.
  • Integration with a pre-trained vision-language model helps generate effective referring prompts for SAM.
  • Text composition tackles complexities in medical descriptions, enhancing clarity and focus on pertinent features.
  • Experiments show significant performance improvements over traditional geometric prompt methods in multiple datasets.

Cite This Study

Zhang et al. (2025) studied this question.

synapsesocial.com/papers/68c199e89b7b07f3a061b77ahttps://doi.org/10.1109/jbhi.2025.3607023
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