AIMC Topic: Coronary Stenosis

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Additional value of deep learning computed tomographic angiography-based fractional flow reserve in detecting coronary stenosis and predicting outcomes.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Deep learning (DL) has achieved great success in medical imaging and could be utilized for the non-invasive calculation of fractional flow reserve (FFR) from coronary computed tomographic angiography (CCTA) (CT-FFR).

Artificial Intelligence in Coronary Computed Tomography Angiography: From Anatomy to Prognosis.

BioMed research international
Cardiac computed tomography angiography (CCTA) is widely used as a diagnostic tool for evaluation of coronary artery disease (CAD). Despite the excellent capability to rule-out CAD, CCTA may overestimate the degree of stenosis; furthermore, CCTA anal...

Direct Quantification of Coronary Artery Stenosis Through Hierarchical Attentive Multi-View Learning.

IEEE transactions on medical imaging
Quantification of coronary artery stenosis on X-ray angiography (XRA) images is of great importance during the intraoperative treatment of coronary artery disease. It serves to quantify the coronary artery stenosis by estimating the clinical morpholo...

Automatic stenosis recognition from coronary angiography using convolutional neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Coronary artery disease, which is mostly caused by atherosclerotic narrowing of the coronary artery lumen, is a leading cause of death. Coronary angiography is the standard method to estimate the severity of coronary artery ...

Artificial intelligence in cardiac radiology.

La Radiologia medica
Artificial intelligence (AI) is entering the clinical arena, and in the early stage, its implementation will be focused on the automatization tasks, improving diagnostic accuracy and reducing reading time. Many studies investigate the potential role ...

Functional cardiac CT-Going beyond Anatomical Evaluation of Coronary Artery Disease with Cine CT, CT-FFR, CT Perfusion and Machine Learning.

The British journal of radiology
The aim of this review is to provide an overview of different functional cardiac CT techniques which can be used to supplement assessment of the coronary arteries to establish the significance of coronary artery stenoses. We focus on cine-CT, CT-FFR,...

Deep learning analysis in coronary computed tomographic angiography imaging for the assessment of patients with coronary artery stenosis.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Recently, deep convolutional neural network has significantly improved image classification and image segmentation. If coronary artery disease (CAD) can be diagnosed through machine learning and deep learning, it will signif...