Resources

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.

A chest x-rays segmentation dataset derived from MIMIC-CXR based on deep learning algorithm and human examination.

Instruction-guided lesion segmentation data for chest X-rays, including 1.1M instruction-answer pairs and 91K segmentation masks covering seven major lesion types.

CheXmask Database is a 657,566 uniformly annotated chest radiographs with segmentation masks. Images were segmented using HybridGNet, with automatic quality control indicated by RCA scores.

Endoscapes2023 enables the development of models for object detection, semantic and instance segmentation, and Critical View of Safety (CVS) prediction, contributing to safe laparoscopic cholecystectomy.

Heart and lung segmentations for 200 MIMIC-CXR/MIMIC-CXR-JPG chest x-rays and heart segmentations for 138 Montgomery County tuberculosis chest X-rays.

This dataset comprises 11,094 converted DICOM and smartphone images of Cardiac Implantable Electronic Devices (CIEDs), collected from 897 patients. It aims to facilitate the development of algorithms for CIED detection and classification.

A curated subset of MIMIC-IV-ECHO providing apical four-chamber cine loops with manual ROI masks, volumetric labels, and ready-to-use MP4/NPZ derivatives for robust LV volume and ejection fraction research.