OmniMedVQA: A New Large-Scale Comprehensive Evaluation Benchmark for Medical LVLM

arXiv:2402.09181v2 Announce Type: replace-cross
Abstract: Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities in various multimodal tasks. However, their potential in the medical domain remains largely unexplored. A significant challenge arises from the scarcity of diverse medical images spanning various modalities and anatomical regions, which is essential in real-world medical applications. To solve this problem, in this paper, we introduce OmniMedVQA, a novel comprehensive medical Visual Question Answering (VQA) benchmark. This benchmark is collected from 73 different medical datasets, including …

arxiv benchmark cs.cv eess.iv evaluation lvlm medical scale type