AIMC Topic: Coronary Vessels

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PlaqueViT: a vision transformer model for fully automatic vessel and plaque segmentation in coronary computed tomography angiography.

European radiology Feb 5, 2025
OBJECTIVES: To develop and evaluate a deep learning model for segmentation of the coronary artery vessels and coronary plaques in coronary computed tomography angiography (CCTA).
Humans Female Reproducibility of Results Aged Sensitivity and Specificity Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Coronary Vessels Plaque, Atherosclerotic Computed Tomography Angiography Male Middle Aged Deep Learning Coronary Angiography
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Prediction of obstructive coronary artery disease using coronary calcification and epicardial adipose tissue assessments from CT calcium scoring scans.

Journal of cardiovascular computed tomography Feb 4, 2025
BACKGROUND: Low-cost/no-cost non-contrast CT calcium scoring (CTCS) exams can provide direct evidence of coronary atherosclerosis. In this study, using features from CTCS images, we developed a novel machine learning model to predict obstructive coro...
Female Reproducibility of Results Risk Factors Aged Male Humans Machine Learning Decision Support Techniques Prognosis Computed Tomography Angiography Pericardium Epicardial Adipose Tissue Predictive Value of Tests Coronary Angiography Middle Aged Coronary Artery Disease Risk Assessment Coronary Vessels Severity of Illness Index Vascular Calcification Adipose Tissue
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A continuous-action deep reinforcement learning-based agent for coronary artery centerline extraction in coronary CT angiography images.

Medical & biological engineering & computing Jan 31, 2025
The lumen centerline of the coronary artery allows vessel reconstruction used to detect stenoses and plaques. Discrete-action-based centerline extraction methods suffer from artifacts and plaques. This study aimed to develop a continuous-action-based...
Artifacts Coronary Vessels Computed Tomography Angiography Reinforcement Machine Learning Humans Algorithms Deep Learning Image Processing, Computer-Assisted Coronary Angiography Coronary Artery Disease
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Segmentation of coronary artery and calcification using prior knowledge based deep learning framework.

Medical physics Jan 29, 2025
BACKGROUND: Computed tomography angiography (CTA) is used to screen for coronary artery calcification. As the coronary artery has complicated structure and tiny lumen, manual screening is a time-consuming task. Recently, many deep learning methods ha...
Coronary Artery Disease Humans Deep Learning Coronary Vessels Image Processing, Computer-Assisted Vascular Calcification Computed Tomography Angiography Calcinosis
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Enhancing quantitative coronary angiography (QCA) with advanced artificial intelligence: comparison with manual QCA and visual estimation.

The international journal of cardiovascular imaging Jan 29, 2025
Artificial intelligence-based quantitative coronary angiography (AI-QCA) was introduced to address manual QCA's limitations in reproducibility and correction process. The present study aimed to assess the performance of an updated AI-QCA solution (MP...
Coronary Vessels Humans Reproducibility of Results Coronary Stenosis Artificial Intelligence Predictive Value of Tests Aged Retrospective Studies Coronary Angiography Male Female Radiographic Image Interpretation, Computer-Assisted Middle Aged Coronary Artery Disease Severity of Illness Index
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Application of deep learning in automated localization and interpretation of coronary artery calcification in oncological PET/CT scans.

The international journal of cardiovascular imaging Jan 13, 2025
Coronary artery calcification (CAC) is a key marker of coronary artery disease (CAD) but is often underreported in cancer patients undergoing non-gated CT or PET/CT scans. Traditional CAC assessment requires gated CT scans, leading to increased radia...
Vascular Calcification Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Automation Humans Coronary Vessels Retrospective Studies Female Neoplasms Reproducibility of Results Deep Learning Aged Predictive Value of Tests Male Coronary Angiography Middle Aged Positron Emission Tomography Computed Tomography
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Diagnostic accuracy in coronary CT angiography analysis: artificial intelligence versus human assessment.

Open heart Jan 11, 2025
BACKGROUND: Visual assessment of coronary CT angiography (CCTA) is time-consuming, influenced by reader experience and prone to interobserver variability. This study evaluated a novel algorithm for coronary stenosis quantification (atherosclerosis im...
Female Reproducibility of Results Aged Male Middle Aged Coronary Stenosis Severity of Illness Index Predictive Value of Tests Coronary Angiography Coronary Artery Disease Radiographic Image Interpretation, Computer-Assisted Observer Variation Humans Coronary Vessels Artificial Intelligence Computed Tomography Angiography Algorithms Retrospective Studies
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End-to-end deep-learning model for the detection of coronary artery stenosis on coronary CT images.

Open heart Jan 11, 2025
PURPOSE: We examined whether end-to-end deep-learning models could detect moderate (≥50%) or severe (≥70%) stenosis in the left anterior descending artery (LAD), right coronary artery (RCA) or left circumflex artery (LCX) in iodine contrast-enhanced ...
Computed Tomography Angiography Coronary Stenosis Aged Male Middle Aged Humans Severity of Illness Index Deep Learning Retrospective Studies Predictive Value of Tests Female Coronary Angiography Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted Coronary Vessels
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Automated stenosis estimation of coronary angiographies using end-to-end learning.

The international journal of cardiovascular imaging Jan 9, 2025
The initial evaluation of stenosis during coronary angiography is typically performed by visual assessment. Visual assessment has limited accuracy compared to fractional flow reserve and quantitative coronary angiography, which are more time-consumin...
Coronary Stenosis Fractional Flow Reserve, Myocardial Middle Aged Severity of Illness Index Deep Learning Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Automation Coronary Vessels Female Reproducibility of Results Aged Male Humans Retrospective Studies
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Segmentation and Vascular Vectorization for Coronary Artery by Geometry-Based Cascaded Neural Network.

IEEE transactions on medical imaging Jan 2, 2025
Segmentation of the coronary artery is an important task for the quantitative analysis of coronary computed tomography angiography (CCTA) images and is being stimulated by the field of deep learning. However, the complex structures with tiny and narr...
Algorithms Image Processing, Computer-Assisted Coronary Angiography Coronary Vessels Computed Tomography Angiography Humans Neural Networks, Computer
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