ArticleScientific data2023
Annotated computed tomography coronary angiogram images and associated data of normal and diseased arteries.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- [A study on three-dimensional reconstruction of coronary arteries and numerical simulation of fractional flow reserve based on deep learning].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026Article
- Optimising Generalisable Deep Learning Models for CT Coronary Segmentation: A Multifactorial Evaluation.Journal of imaging informatics in medicine · 2026Article
- Physics-informed graph neural networks for real-time prediction of wall shear stress in stenotic coronary arteries.Scientific reports · 2026Article
- Geometric-topological deep transfer learning for precise vessel segmentation in 3D medical volumes.NPJ digital medicine · 2026Article
- High-intensity helical flow: a double-edged sword in coronary artery haemodynamics.Royal Society open science · 2025Article
- Article
- A new understanding of coronary curvature and haemodynamic impact on the course of plaque onset and progression.Royal Society open science · 2024Article
- Mining multi-center heterogeneous medical data with distributed synthetic learning.Nature communications · 2023Article
- Annotated computed tomography coronary angiogram images and associated data of normal and diseased arteries.Scientific data · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 the Coronary Atlas. 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.