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Background. Coronary artery calcium (CAC) is a powerful predictor of major adverse cardiovascular events (MACE). Traditional Agatston score simply sums the calcium, albeit in a non-linear way, leaving room for improved calcification…

Quantitative Methods · Quantitative Biology 2023-08-24 Ammar Hoori , Sadeer Al-Kindi , Tao Hu , Yingnan Song , Hao Wu , Juhwan Lee , Nour Tashtish , Pingfu Fu , Robert Gilkeson , Sanjay Rajagopalan , David L. Wilson

Women are underdiagnosed and undertreated for cardiovascular disease. Automatic quantification of breast arterial calcification on screening mammography can identify women at risk for cardiovascular disease and enable earlier treatment and…

Cardiovascular disease causes high rates of mortality worldwide. Coronary artery calcium (CAC) scoring is a powerful tool to stratify the risk of atherosclerotic cardiovascular disease. Current scoring practices require time-intensive…

Computer Vision and Pattern Recognition · Computer Science 2025-11-12 Lachlan Nguyen , Aidan Cousins , Arcot Sowmya , Hugh Dixson , Sonit Singh

As a potential non-invasive biomarker for ischaemic stroke, intracranial arterial calcification (IAC) could be used for stroke risk assessment on CT head scans routinely acquired for other reasons (e.g. trauma, confusion). Artificial…

Image and Video Processing · Electrical Eng. & Systems 2025-07-03 Benjamin Jin , Maria del C. Valdés Hernández , Alessandro Fontanella , Wenwen Li , Eleanor Platt , Paul Armitage , Amos Storkey , Joanna M. Wardlaw , Grant Mair

Despite coronary artery calcium scoring being considered a largely solved problem within the realm of medical artificial intelligence, this paper argues that significant improvements can still be made. By shifting the focus from pathology…

Coronary artery calcium (CAC) is a significant marker of atherosclerosis and cardiovascular events. In this work we present a system for the automatic quantification of calcium score in ECG-triggered non-contrast enhanced cardiac computed…

Computer Vision and Pattern Recognition · Computer Science 2017-10-10 G. Santini , D. Della Latta , N. Martini , G. Valvano , A. Gori , A. Ripoli , C. L. Susini , L. Landini , D. Chiappino

Calcium scoring, a process in which arterial calcifications are detected and quantified in CT, is valuable in estimating the risk of cardiovascular disease events. Especially when used to quantify the extent of calcification in the coronary…

Image and Video Processing · Electrical Eng. & Systems 2021-05-27 Sanne G. M. van Velzen , Nils Hampe , Bob D. de Vos , Ivana Išgum

Non-contrast computed tomography calcium scoring (CTCS) is widely recognized as an effective tool for cardiovascular risk stratification. This study aimed to develop a novel machine learning framework for predicting myocardial ischemia from…

Machine Learning · Computer Science 2026-05-22 Juhwan Lee , Sadeer Al-Kindi , Ammar Hoori , Tao Hu , Hao Wu , Justin N. Kim , Robert Gilkeson , Sanjay Rajagopalan , David L. Wilson

Cardiovascular Diseases (CVDs) are the leading cause of death worldwide, taking 17.9 million lives annually. Abdominal Aortic Calcification (AAC) is an established marker for CVD, which can be observed in lateral view Vertebral Fracture…

Computer Vision and Pattern Recognition · Computer Science 2024-09-27 Zaid Ilyas , Afsah Saleem , David Suter , Siobhan Reid , John Schousboe , William Leslie , Joshua Lewis , Syed Zulqarnain Gilani

The presence of plaques in the coronary arteries is a major risk to the patients' life. In particular, non-calcified plaques pose a great challenge, as they are harder to detect and more likely to rupture than calcified plaques. While…

We report an object tracking algorithm that combines geometrical constraints, thresholding, and motion detection for tracking of the descending aorta and the network of major arteries that branch from the aorta including the iliac and…

Image and Video Processing · Electrical Eng. & Systems 2019-12-19 Liang Zhao , Brendan Odigwe , Susan Lessner , Daniel G. Clair , Firas Mussa , Homayoun Valafar

Coronary artery calcification (CAC) is a strong predictor of cardiovascular risk but remains underutilized in clinical routine thoracic imaging due to the need for dedicated imaging protocols and manual annotation. We present DeepCAC2, a…

Image and Video Processing · Electrical Eng. & Systems 2026-03-27 Leonard Nürnberg , Simon Bernatz , Borek Foldyna , Michael T. Lu , Andrey Fedorov , Hugo JWL Aerts

Atherosclerosis, a chronic inflammatory disease affecting the large arteries, presents a global health risk. Accurate analysis of diagnostic images, like computed tomographic angiograms (CTAs), is essential for staging and monitoring the…

Image and Video Processing · Electrical Eng. & Systems 2023-11-28 Alireza Bagheri Rajeoni , Breanna Pederson , Daniel G. Clair , Susan M. Lessner , Homayoun Valafar

Early detection and analysis of calcifications in mammogram images is crucial in a breast cancer diagnosis workflow. Management of calcifications that require immediate follow-up and further analyzing its benignancy or malignancy can result…

Image and Video Processing · Electrical Eng. & Systems 2022-12-12 Adarsh Bhandary Panambur , Prathmesh Madhu , Andreas Maier

Coronary artery calcium (CAC) scoring plays a crucial role in the early detection and risk stratification of coronary artery disease (CAD). In this study, we focus on non-contrast coronary computed tomography angiography (CCTA) scans, which…

Accurate and timely identification of pulmonary nodules on chest X-rays can differentiate between life-saving early treatment and avoidable invasive procedures. Calcification is a definitive indicator of benign nodules and is the primary…

Image and Video Processing · Electrical Eng. & Systems 2025-08-19 Hyeonjin Choi , Yang-gon Kim , Dong-yeon Yoo , Ju-sung Sun , Jung-won Lee

Assessing coronary artery plaque segments in coronary CT angiography scans is an important task to improve patient management and clinical outcomes, as it can help to decide whether invasive investigation and treatment are necessary. In…

Cardiovascular disease (CVD) remains the leading global cause of mortality, yet current risk stratification methods often fail to detect early, subclinical changes. Previous studies have generally not integrated retinal microvasculature…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Inamullah , Ernesto Elias Vidal Rosas , Imran Razzak , Shoaib Jameel

Heavy smokers undergoing screening with low-dose chest CT are affected by cardiovascular disease as much as by lung cancer. Low-dose chest CT scans acquired in screening enable quantification of atherosclerotic calcifications and thus…

Computer Vision and Pattern Recognition · Computer Science 2018-02-06 Nikolas Lessmann , Bram van Ginneken , Majd Zreik , Pim A. de Jong , Bob D. de Vos , Max A. Viergever , Ivana Išgum

We propose a method to classify cardiac pathology based on a novel approach to extract image derived features to characterize the shape and motion of the heart. An original semi-supervised learning procedure, which makes efficient use of a…

Computer Vision and Pattern Recognition · Computer Science 2019-03-29 Qiao Zheng , Hervé Delingette , Nicholas Ayache
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