MIMIC-IV-ECHO-Ext-MIMICEchoQA: A Benchmark Dataset for Echocardiogram-Based Visual Question Answering

We present MIMICEchoQA, a benchmark dataset for echocardiogram-based question
answering, built from the publicly available MIMIC-IV-ECHO database. Each
echocardiographic study was paired with the closest discharge summary within a
7-day window, and the transthoracic echocardiography (TTE) and ECHO sections
were extracted to serve as proxies for cardiologist-authored diagnostic
reports. DICOM videos were converted to `.mp4` format, and a language model
was used to generate multi-turn, closed-ended Q/A pairs grounded in these
reports. To ensure anatomical consistency, a view classification model was
used to label each video by its echocardiographic view (e.g., A4C, A3C),
enabling the filtering of questions referencing structures not visible in the
corresponding video. All generated Q/A pairs were manually reviewed by two
board-certified cardiologists to ensure clinical validity. The final dataset
consists of 622 high-quality, view-consistent Q/A pairs aligned with real-
world echocardiogram videos, offering a valuable resource for developing and
evaluating models in echocardiographic visual question answering.