Tri-VQA: Triangular Reasoning Medical Visual Question Answering for Multi-Attribute Analysis

Med-VQA, intersecting medicine and VQA, is a challenging field offering benefits like patient engagement and clinical collaboration. However, current joint embedding methods lack explanation of reasoning, undermining VQA credibility. In this paper, motivated by causal effect, we propose a novel Triangular Reasoning VQA (Tri-VQA) framework, which constructs reverse causal questions from the perspective of "Why this answer?" to elucidate the source of the answer and stimulate more reasonable forward reasoning processes. We evaluate our method on EUS multi-attribute annotated datasets from five centers and medical VQA datasets, demonstrating superior performance. Our codes and pre-trained models are available at https://github.com/hahaha111111/Tri-VQA.