AIMC Topic: Coronary Angiography

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Learning tree-structured representation for 3D coronary artery segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Extensive research has been devoted to the segmentation of the coronary artery. However, owing to its complex anatomical structure, it is extremely challenging to automatically segment the coronary artery from 3D coronary computed tomography angiogra...

Performance of a deep learning algorithm for the evaluation of CAD-RADS classification with CCTA.

Atherosclerosis
BACKGROUND AND AIMS: Artificial intelligence (AI) is increasing its role in diagnosis of patients with suspicious coronary artery disease. The aim of this manuscript is to develop a deep convolutional neural network (CNN) to classify coronary compute...

Learning physical properties in complex visual scenes: An intelligent machine for perceiving blood flow dynamics from static CT angiography imaging.

Neural networks : the official journal of the International Neural Network Society
Humans perceive physical properties such as motion and elastic force by observing objects in visual scenes. Recent research has proven that computers are capable of inferring physical properties from camera images like humans. However, few studies pe...

Deep learning segmentation of major vessels in X-ray coronary angiography.

Scientific reports
X-ray coronary angiography is a primary imaging technique for diagnosing coronary diseases. Although quantitative coronary angiography (QCA) provides morphological information of coronary arteries with objective quantitative measures, considerable tr...

Evaluation of an AI-based, automatic coronary artery calcium scoring software.

European radiology
OBJECTIVES: To evaluate an artificial intelligence (AI)-based, automatic coronary artery calcium (CAC) scoring software, using a semi-automatic software as a reference.

Deep Learning Analysis of Coronary Arteries in Cardiac CT Angiography for Detection of Patients Requiring Invasive Coronary Angiography.

IEEE transactions on medical imaging
In patients with obstructive coronary artery disease, the functional significance of a coronary artery stenosis needs to be determined to guide treatment. This is typically established through fractional flow reserve (FFR) measurement, performed duri...

Correlation of machine learning computed tomography-based fractional flow reserve with instantaneous wave free ratio to detect hemodynamically significant coronary stenosis.

Clinical research in cardiology : official journal of the German Cardiac Society
BACKGROUND: Fractional flow reserve based on coronary CT angiography (CT-FFR) is gaining importance for non-invasive hemodynamic assessment of coronary artery disease (CAD). We evaluated the on-site CT-FFR with a machine learning algorithm (CT-FFR) f...