Resources

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.

The MS-CXR-T is a multimodal benchmark that enhances the MIMIC-CXR v2 dataset by including expert-verified annotations. Its goal is to evaluate biomedical visual-language processing models in terms of temporal semantics extracted from image and text.

Multimodal dataset with 166k samples for vision-based applications with a smart walker used in gait and posture rehabilitation. It is equipped with a pair of Depth cameras with data synchronized with an inertial MoCap system worn by the participant.

CXLSeg dataset: Chest X-ray with Lung Segmentation, a comparatively large dataset of segmented Chest X-ray radiographs based on the MIMIC-CXR dataset. This contains segmentation results of 243,324 frontal view images and corresponding masks.

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

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.

1402 kinematic recordings of twenty-two semi-professional actors expressing emotions such as happiness, sadness, anger, fear, disgust, and surprise.

This is the first Brazilian Multilabel Ophthalmological Dataset with demographic information and retinal photos labeled images according to anatomical parameters, quality control, and presumed diagnosis.

The project aims at collecting a dataset using eye-tracking technology to understand the 12-lead electrocardiogram interpretation visual behavior for medical practitioners and students with different expertise levels.

This dataset contains 3032 cases of eye-tracking data collected while five radiologists dictated reports for frontal chest x-rays, synchronized timestamped dictation transcription, and manual labels for validation of localization of abnormalities.