AIMC Topic: Coronary Vessels

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Improvement in Image Quality and Visibility of Coronary Arteries, Stents, and Valve Structures on CT Angiography by Deep Learning Reconstruction.

Korean journal of radiology
OBJECTIVE: This study aimed to investigate whether a deep learning reconstruction (DLR) method improves the image quality, stent evaluation, and visibility of the valve apparatus in coronary computed tomography angiography (CCTA) when compared with f...

Federated machine learning for a facilitated implementation of Artificial Intelligence in healthcare - a proof of concept study for the prediction of coronary artery calcification scores.

Journal of integrative bioinformatics
The implementation of Artificial Intelligence (AI) still faces significant hurdles and one key factor is the access to data. One approach that could support that is federated machine learning (FL) since it allows for privacy preserving data access. F...

Coronary Artery Stent Evaluation by CTA: Impact of Deep Learning Reconstruction and Subtraction Technique.

AJR. American journal of roentgenology
Coronary CTA with hybrid iterative reconstruction (HIR) is prone to false-positive results for in-stent restenosis due to stent-related blooming artifact. The purpose of this study is to assess the impact of deep learning reconstruction (DLR), subt...

A Deep Learning-based Method to Extract Lumen and Media-Adventitia in Intravascular Ultrasound Images.

Ultrasonic imaging
Intravascular ultrasound (IVUS) imaging allows direct visualization of the coronary vessel wall and is suitable for assessing atherosclerosis and the degree of stenosis. Accurate segmentation and lumen and median-adventitia (MA) measurements from IVU...

A novel end-to-end deep learning solution for coronary artery segmentation from CCTA.

Medical physics
PURPOSE: Coronary computed tomographic angiography (CCTA) plays a vital role in the diagnosis of cardiovascular diseases, among which automatic coronary artery segmentation (CAS) serves as one of the most challenging tasks. To computationally assist ...

Towards automated coronary artery segmentation: A systematic review.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Vessel segmentation is the first processing stage of 3D medical images for both clinical and research use. Current segmentation methods are tedious and time consuming, requiring significant manual correction and hence are in...

Explainable deep learning algorithm for distinguishing incomplete Kawasaki disease by coronary artery lesions on echocardiographic imaging.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Incomplete Kawasaki disease (KD) has often been misdiagnosed due to a lack of the clinical manifestations of classic KD. However, it is associated with a markedly higher prevalence of coronary artery lesions. Identifying cor...

Deep learning-based atherosclerotic coronary plaque segmentation on coronary CT angiography.

European radiology
OBJECTIVES: Volumetric evaluation of coronary artery disease (CAD) allows better prediction of cardiac events. However, CAD segmentation is labor intensive. Our objective was to create an open-source deep learning (DL) model to segment coronary plaqu...