ARCADE: Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs Dataset Phase 1

ARCADE: Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs Dataset Phase 1 consists of two datasets of XCA images for each of two tasks of ARCADE challenge. The first task includes in total 1200 coronary vessel tree images, which are divided into train(1000) and validation(200) groups, images for training are followed with annotations, depicting the division of a heart into 26 different regions based on the Syntax Score methodology[1]. Similarly, the second task includes a different set of 1200 images with same train-val division proportion with annotated regions containing atherosclerotic plaques. This dataset, carefully annotated by medical experts, enables scientists to actively contribute towards the advancement of an automated risk assessment system for patients with CAD. Zip file has 2 main folders: 1. segmentation_dataset , 2. stenosis_dataset 1. segmentation_dataset consists of seg_train and seg_val folders. Seg_train folder has images folder, where 1000 XCA images are provided, and annotations folder, where annotation of 1000 images in COCO format is provided. Seg_val folder has images folder, where 200 XCA images are provided. 2. stenosis_dataset consists of seg_train and seg_val folders. Seg_train folder has images folder, where 1000 XCA images are provided, and annotations folder, where annotation of 1000 images in COCO format is provided. Seg_val folder has images folder, where 200 XCA images are provided. The corresponding Dataset Article will be provided later. [1] Syntax score segment definitions. https://syntaxscore.org/index.php/tutorial/definitions/14-appendix-i-segment-definition