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

Authors: Maxim Popov; Akmaral Amanturdieva; Nuren Zhaksylyk; Alsabir Alkanov; Adilbek Saniyazbekov; Temirgali Aimyshev; Eldar Ismailov; +8 Authors

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

Abstract

ARCADE: Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs Dataset Phase 2 consist of two folders with 300 images in each of them as well as annotations. 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. dataset_final_phase , 2. dataset_phase_1 Structure of dataset_final_phase: 2 folders: 1. test cases stenosis with 300 images with annotations 2. test case segmentation with 300 images with annotations Structure of dataset_phase_1: 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 and annotations 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 and annotations 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-definitions

Keywords

multiclass segmentation, medical imaging, coronary artery segmentation, stenosis detection and localization, coronary artery disease

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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