Resources


Database Credentialed Access

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

Mingjie Li, Wenjia Cai, Rui Liu, Yuetian Weng, Tengfei Liu, 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 medical report generation vision and language explainable and reliable evaluation

Published: Jan. 21, 2025. Version: 1.1.0


Database Credentialed Access

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

Mingjie Li, Wenjia Cai, Rui Liu, Yuetian Weng, Tengfei Liu, 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 medical report generation vision and language explainable and reliable evaluation

Published: Jan. 21, 2025. Version: 1.1.0


Database Restricted Access

LATTE-CXR: Locally Aligned TexT and imagE, Explainable dataset for Chest X-Rays

Elham Ghelichkhan, Tolga Tasdizen

This dataset includes bounding box-statement pairs for chest X-ray images, derived from radiologists’ eye-tracking data (for explainability) and annotations, for local visual-language models.

eye-tracking chest x-ray dataset automatically generated dataset caption-guided object detection localization image captioning with region-level description grounded radiology report generation phrase grounding xai multi-modal learning local visual-language models

Published: Feb. 4, 2025. 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.

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

Published: July 13, 2021. Version: 1.0.0


Database Credentialed Access

Eye Gaze Data for Chest X-rays

Alexandros Karargyris, Satyananda Kashyap, Ismini Lourentzou, Joy Wu, Matthew Tong, Arjun Sharma, Shafiq Abedin, David Beymer, Vandana Mukherjee, Elizabeth Krupinski, Mehdi Moradi

This dataset was a collected using an eye tracking system while a radiologist interpreted and read 1,083 public CXR images. The dataset contains the following aligned modalities: image, transcribed report text, dictation audio and eye gaze data.

convolutional network heatmap eye tracking explainability audio chest cxr chest x-ray machine learning radiology deep learning multimodal

Published: Sept. 12, 2020. Version: 1.0.0


Database Open Access

Image-derived cardiomegaly biomarker values for 96K chest X-rays in MIMIC-CXR/MIMIC-CXR-JPG

Benjamin Duvieusart, Felix Krones, Guy Parsons, Lionel Tarassenko, Bartlomiej W Papiez, Adam Mahdi

Automatically extracted cardiomegaly biomarkers - cardiothoracic ratio (CTR) and cardiopulmonary area ratio (CPAR) - for all posterior-anterior chest x-ray scans in MIMIC-CXR/MIMIC-CXR-JPG.

biomarkers mimic-cxr cpar ctr cardiomegaly

Published: Aug. 23, 2024. 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.

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

Published: July 13, 2021. Version: 1.0.0


Database Credentialed Access

Eye Gaze Data for Chest X-rays

Alexandros Karargyris, Satyananda Kashyap, Ismini Lourentzou, Joy Wu, Matthew Tong, Arjun Sharma, Shafiq Abedin, David Beymer, Vandana Mukherjee, Elizabeth Krupinski, Mehdi Moradi

This dataset was a collected using an eye tracking system while a radiologist interpreted and read 1,083 public CXR images. The dataset contains the following aligned modalities: image, transcribed report text, dictation audio and eye gaze data.

convolutional network heatmap eye tracking explainability audio chest cxr chest x-ray machine learning radiology deep learning multimodal

Published: Sept. 12, 2020. Version: 1.0.0


Challenge Open Access

RR Interval Time Series Modeling: The PhysioNet/Computing in Cardiology Challenge 2002

We are pleased to announce the third in our annual series of challenges from PhysioNet and Computers in Cardiology. We received many suggestions for challenge topics, and encourage you to write to us with further suggestions. We chose the topic for…

interbeat rr interval challenge

Published: Feb. 14, 2002. Version: 1.0.0