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Updated: May 25, 2025

Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans
Published on: August 28, 2018
CoronaryDominance: Angiogram dataset for coronary dominance classification
Ivan Kruzhilov1,2, Gleb Mazanov3, Alexander Ponomarchuk4
1Applied mathematics and artificial intelligence, Moscow Power Engineering Institute, 14, Krasnokazarmennaya, Moscow, 111250, Russia. kruzhilovis@mpei.ru.
Abstract:
We release a new dataset containing invasive coronary angiograms for the coronary dominance classification task, an essential aspect of SYNTAX score estimation for assessing the severity of coronary artery disease. The dataset contains 1,574 angiographic studies, a set of X-ray multi-view videos classified as right or left dominant. The dataset has three parts: main, real distribution, and domain shift. Each study in the main dataset falls into five categories: normal, poor quality, artifact, high uncertainty, or right coronary artery (RCA) occlusion. These tags help classify the dominance more accurately and allow for uncertainty estimation and outlier detection. In the real distribution part, there are 400 randomly selected studies. In contrast the domain shift part includes studies from an interventional angiography system that differs from that used in the main and real distribution parts.
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