ArticleDiagnostics (Basel, Switzerland)2021
End-to-End, Pixel-Wise Vessel-Specific Coronary and Aortic Calcium Detection and Scoring Using Deep Learning.
Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Cross-Domain Knowledge Transfer from Expert-Annotated Gated CT via Synthetic Ungated CT Improves Coronary Artery Calcium Scoring on CT Attenuation Correction Scans.medRxiv : the preprint server for health sciences · 2026Article
- CycleGAN-based image-to-image translation for synthetic contrast enhancement in non-contrast cardiac CT: a ViT-CNN hybrid deep learning approach.BMC medical informatics and decision making · 2026Article
- A New Aortic Valve Calcium Scoring Framework for Automatic Calcification Detection in Echocardiography.Journal of imaging informatics in medicine · 2026Article
- Pericoronary Adipose Tissue Attenuation in Patients with Future Acute Coronary Syndromes: The ICONIC Study.Radiology. Cardiothoracic imaging · 2025Observational
- Cohort profile: AI-driven national Platform for CCTA for clinicaL and industriaL applicatiOns (APOLLO).BMJ open · 2024Article
- Automated vessel-specific coronary artery calcification quantification with deep learning in a large multi-centre registry.European heart journal. Cardiovascular Imaging · 2024Article
- Role and progress of artificial intelligence in radiodiagnosing vascular calcification: a narrative review.Annals of translational medicine · 2023Review
- Comparing the pooled cohort equations and coronary artery calcium scores in a symptomatic mixed Asian cohort.Frontiers in cardiovascular medicine · 2023Article
- Coronary Calcium Scoring with First Generation Dual-Source Photon-Counting CT-First Evidence from Phantom and In-Vivo Scans.Diagnostics (Basel, Switzerland) · 2021Article
- Deep-Learning-Based Detection of Cranio-Spinal Differences between Skeletal Classification Using Cephalometric Radiography.Diagnostics (Basel, Switzerland) · 2021Article
- Calcium scoring in low-dose ungated chest CT scans using convolutional long-short term memory networks.Proceedings of SPIE--the International Society for Optical EngineeringArticle
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Conventional scoring and identification methods for coronary artery calcium (CAC) and aortic calcium (AC) result in information loss from the original image and can be time-consuming. In this study, we sought to demonstrate an end-to-end deep learning model as an alternative to the conventional methods. Scans of 377 patients with no history of coronary artery disease (CAD) were obtained and annotated. A deep learning model was trained, tested and validated in a 60:20:20 split. Within the cohort, mean age was 64.2 ± 9.8 years, and 33% were female. Left anterior descending, right coronary artery, left circumflex, triple vessel, and aortic calcifications were present in 74.87%, 55.82%, 57.41%, 46.03%, and 85.41% of patients respectively. An overall Dice score of 0.952 (interquartile range 0.921, 0.981) was achieved. Stratified by subgroups, there was no difference between male (0.948, interquartile range 0.920, 0.981) and female (0.965, interquartile range 0.933, 0.980) patients (
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