English(EN) Exploring the Capabilities of Large Language Model Encoders for Image-Text Retrieval in Chest X-rays

大型语言模型编码器改进胸部X射线图像文本检索

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-02 04:00

研究人员开发了一种领域适应的大型语言模型编码器，以改进胸部X射线的图像文本检索。该方法通过训练编码器生成稳健的文本嵌入，解决了放射学报告风格多变且缩写的问题。当集成到双塔对比框架中时，该模型增强了X射线图像与其对应报告之间的对齐，从而提高了检索准确性和跨不同数据集的泛化能力。 AI

影响增强了医学影像的多模态学习，有望提高放射学诊断的准确性和效率。

排序理由该集群包含一篇学术论文，详细介绍了特定医学领域多模态学习的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Hanbin Ko, Gihun Cho, Inhyeok Baek, Donguk Kim, Joonbeom Koo, Changi Kim, Dongheon Lee, Chang Min Park · 2026-06-02 04:00

探索大型语言模型编码器在胸部X光图像-文本检索中的能力

arXiv:2509.15234v2 Announce Type: replace Abstract: Multimodal learning from paired medical images and clinical text is a central challenge in medical data-driven informatics, where effective cross-modal alignment is critical for scalable analysis and retrieval. In chest radiogra…