ClinKD: Cross-Modal Clinical Knowledge Distiller For Multi-Task Medical Images

• URL: http://arxiv.org/abs/2502.05928v3
• Date: Sat, 19 Apr 2025 14:13:40 GMT
• Title: ClinKD: Cross-Modal Clinical Knowledge Distiller For Multi-Task Medical Images
• Authors: Hongyu Ge, Longkun Hao, Zihui Xu, Zhenxin Lin, Bin Li, Shoujun Zhou, Hongjin Zhao, Yihang Liu,
• Abstract summary: Cross-Modal Clinical Knowledge Distiller (ClinKD) designed to enhance image-text alignment and establish more effective medical knowledge adaptation mechanisms.<n>ClinKD achieves state-of-the-art performance on the Med-GRIT-270k dataset, a challenging medical benchmark containing fine-grained multi-task QA pairs.
• Score: 4.353855760968461
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Medical Visual Question Answering (Med-VQA) represents a critical and challenging subtask within the general VQA domain. Despite significant advancements in general Visual Question Answering (VQA), multimodal large language models (MLLMs) still exhibit substantial limitations when handling multi-task VQA scenarios. These limitations manifest through erroneous spatial localization and misinterpretation of medical images, which primarily arise from two fundamental issues: inadequate image-text alignment and insufficient medical knowledge in general-purpose MLLMs for specialized medical applications. To address these issues, we introduce the Cross-Modal Clinical Knowledge Distiller (ClinKD), an innovative framework designed to enhance image-text alignment and establish more effective medical knowledge adaptation mechanisms, which enables MLLMs to adapt to medical knowledge. Our extensive experimental evaluations demonstrate that the ClinKD achieves state-of-the-art performance on the Med-GRIT-270k dataset, a challenging medical benchmark containing fine-grained multi-task QA pairs. The results indicate that our approach not only significantly improves image-text alignment but also effectively enables MLLMs to adapt to the medical knowledge. The source code for ClinKD is available at: https://github.com/overloadedHenry/ClinKD.

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