PhysioNet Index

Database Credentialed Access

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

Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez Valle, Hoifung Poon, Ozan Oktay

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.

chest x-ray vision-language processing

Published: May 16, 2022. Version: 0.1

Database Credentialed Access

FFA-IR: Towards an Explainable and Reliable Medical Report Generation Benchmark

Mingjie Li, Wenjia Cai, Rui Liu, Yuetian Weng, Xiaoyun Zhao, Cong Wang, Xin Chen, Zhong Liu, Caineng Pan, Mengke Li, Yingfeng Zheng, Yizhi Liu, Flora Salim, Karin Verspoor, Xiaodan Liang, Xiaojun Chang

Benchmark dataset for report generation based on fundus fluorescein angiography images and reports.

fundus fluorescein angiography explainable and reliable evaluation vision and language medical report generation

Published: Sept. 21, 2021. Version: 1.0.0

Database Credentialed Access

Chest ImaGenome Dataset

Joy Wu, Nkechinyere Agu, Ismini Lourentzou, Arjun Sharma, Joseph Paguio, Jasper Seth Yao, Edward Christopher Dee, William Mitchell, Satyananda Kashyap, Andrea Giovannini, Leo Anthony Celi, Tanveer Syeda-Mahmood, Mehdi Moradi

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.

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