Resources


Database Credentialed Access

MedVH: Towards Systematic Evaluation of Hallucination for Large Vision Language Models in the Medical Context

Zishan Gu, Jiayuan Chen, Fenglin Liu, et al.

MedVH provides a visual hallucination evaluation benchmark for large language models in the medical context. It formulates tests using chest X-ray images, including multi-choice question answering and long-text generation tasks.

Published: Dec. 10, 2025. Version: 1.0.1

Database Credentialed Access

MS-CXR: Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, et al.

MS-CXR is a new dataset containing 1162 chest X-ray bounding box labels paired with radiology text descriptions, annotated and verified by two board-certified radiologists.

vision-language processing chest x-ray phrase grounding localization

Published: Nov. 15, 2024. Version: 1.1.0

Database Credentialed Access

CXReasonBench: A Benchmark for Evaluating Structured Diagnostic Reasoning in Chest X-rays

Hyungyung Lee, Geon Choi, Jung Oh Lee, et al.

CheXStruct is an automated pipeline that derives structured diagnostic reasoning steps from chest X-rays. CXReasonBench builds on this to evaluate whether models perform clinically grounded, multi-step reasoning beyond final diagnoses.

evaluation chest x-ray benchmark structured chest x-ray qa intermediate reasoning steps structured reasoning grounded reasoning diagnostic reasoning structured diagnostic pipeline

Published: Oct. 23, 2025. Version: 1.0.1

Database Credentialed Access

LLaVA-Rad MIMIC-CXR Annotations

Juan Manuel Zambrano Chaves, Shih-Cheng Huang, Yanbo Xu, et al.

This dataset provides GPT-4 extracted sections of radiology reports from MIMIC-CXR, complementing rule-based section extractions with additional reports with findings, and removing references to priors from findings.

Published: Jan. 24, 2025. Version: 1.0.0

Database Credentialed Access

RaDialog Instruct Dataset

Chantal Pellegrini, Ege Özsoy, Benjamin Busam, et al.

Image-based instruct data for Chest X-Ray understanding and analysis.

medical image understaning radiology chatbot radiology report generation radiology assistant large vision-language models

Published: July 12, 2024. Version: 1.1.0

Database Credentialed Access

MIMIC-Ext-MIMIC-CXR-VQA: A Complex, Diverse, And Large-Scale Visual Question Answering Dataset for Chest X-ray Images

Seongsu Bae, Daeun Kyung, Jaehee Ryu, et al.

We introduce MIMIC-Ext-MIMIC-CXR-VQA, a complex, diverse, and large-scale dataset designed for Visual Question Answering (VQA) tasks within the medical domain, focusing primarily on chest radiographs.

question answering machine learning electronic health records evaluation chest x-ray radiology deep learning benchmark multimodal visual question answering

Published: July 19, 2024. Version: 1.0.0

Database Credentialed Access

RadVLM Instruction Dataset

Nicolas Deperrois, Hidetoshi Matsuo, Samuel Ruiperez-Campillo, et al.

This dataset is designed to construct RadVLM, a vision–language model for chest X-ray interpretation. It includes instruction data for tasks such as report generation, abnormality detection, and region grounding, and multitask conversation.

chest x-rays vision-language models medical ai

Published: Sept. 25, 2025. Version: 1.0.0

Database Credentialed Access

Chest ImaGenome Dataset

Joy Wu, Nkechinyere Agu, Ismini Lourentzou, et al.

The Chest ImaGenome dataset is a scene graph dataset with additional chronological comparison relations for chest X-rays. It is automatically derived from the MIMIC-CXR dataset. A manually annotated gold standard is also available for 500 patients.

scene graph visual dialogue object detection semantic reasoning bounding box knowledge graph explainability reasoning relation extraction chest disease progression cxr machine learning chest x-ray radiology deep learning multimodal visual question answering

Published: July 13, 2021. Version: 1.0.0