Computed tomography coronary angiogram images, annotations and associated data of normal and diseased arteries
This dataset addresses a gap for researchers in medical imaging and computational modeling by offering detailed coronary artery data, though it is incremental as it builds on existing imaging methods.
The authors tackled the lack of a public dataset for coronary artery analysis by providing CTCA images, annotations, and associated data for 20 normal and 20 diseased cases, enabling research in areas like 3D printing and algorithm development.
Computed Tomography Coronary Angiography (CTCA) is a non-invasive method to evaluate coronary artery anatomy and disease. CTCA is ideal for geometry reconstruction to create virtual models of coronary arteries. To our knowledge there is no public dataset that includes centrelines and segmentation of the full coronary tree. We provide anonymized CTCA images, voxel-wise annotations and associated data in the form of centrelines, calcification scores and meshes of the coronary lumen in 20 normal and 20 diseased cases. Images were obtained along with patient information with informed, written consent as part of Coronary Atlas (https://www.coronaryatlas.org/). Cases were classified as normal (zero calcium score with no signs of stenosis) or diseased (confirmed coronary artery disease). Manual voxel-wise segmentations by three experts were combined using majority voting to generate the final annotations. Provided data can be used for a variety of research purposes, such as 3D printing patient-specific models, development and validation of segmentation algorithms, education and training of medical personnel and in-silico analyses such as testing of medical devices.