LIMITR: Leveraging Local Information for Medical Image-Text Representation

• URL: http://arxiv.org/abs/2303.11755v1
• Date: Tue, 21 Mar 2023 11:20:34 GMT
• Title: LIMITR: Leveraging Local Information for Medical Image-Text Representation
• Authors: Gefen Dawidowicz, Elad Hirsch, Ayellet Tal
• Abstract summary: This paper focuses on chest X-ray images and their corresponding radiological reports. It presents a new model that learns a joint X-ray image & report representation.
• Score: 17.102338932907294
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Medical imaging analysis plays a critical role in the diagnosis and treatment of various medical conditions. This paper focuses on chest X-ray images and their corresponding radiological reports. It presents a new model that learns a joint X-ray image & report representation. The model is based on a novel alignment scheme between the visual data and the text, which takes into account both local and global information. Furthermore, the model integrates domain-specific information of two types -- lateral images and the consistent visual structure of chest images. Our representation is shown to benefit three types of retrieval tasks: text-image retrieval, class-based retrieval, and phrase-grounding.

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