Medical-Diff-VQA: A Large-Scale Medical Dataset for Difference Visual Question Answering on Chest X-Ray Images

The task of Difference Visual Question Answering involves answering questions
about the difference between a pair of main and reference images. This process
is consistent with the radiologist's diagnosis practice that compares the
current image with the reference before concluding the report. We've assembled
a new dataset, called Medical-Diff-VQA, for this purpose. Unlike previous
medical VQA datasets, ours is the first one designed specifically for the
Difference Visual Question Answering task, with questions crafted to suit the
Assessment-Diagnosis-Intervention-Evaluation treatment procedure employed by
medical professionals. The Medical-Diff-VQA dataset, a derivative of the
MIMIC-CXR dataset, consists of questions categorized into seven categories:
abnormality (145,421), location (84,193), type (27,478), level (67,296), view
(56,265), presence (155,726), and difference(164,324). The 'difference'
questions are specifically for comparing two images. In total, the Medical-
Diff-VQA dataset contains 700,703 question-answer pairs derived from 164,324
pairs of main and reference images.