AIMC Topic: Coronary Vessels
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Segmenting 3D geometry of left coronary artery from coronary CT angiography using deep learning for hemodynamic evaluation.
Biomedical physics & engineering express
Nov 8, 2022
While coronary CT angiography (CCTA) is crucial for detecting several coronary artery diseases, it fails to provide essential hemodynamic parameters for early detection and treatment. These parameters can be easily obtained by performing computationa...
Deep learning-based prediction of coronary artery stenosis resistance.
American journal of physiology. Heart and circulatory physiology
Oct 21, 2022
Coronary artery stenosis resistance (SR) is a key factor for noninvasive calculations of fractional flow reserve derived from coronary CT angiography (FFR). Existing computational fluid dynamics (CFD) methods, including three-dimensional (3-D) comput...
CAR-Net: A Deep Learning-Based Deformation Model for 3D/2D Coronary Artery Registration.
IEEE transactions on medical imaging
Sep 30, 2022
Percutaneous coronary intervention is widely applied for the treatment of coronary artery disease under the guidance of X-ray coronary angiography (XCA) image. However, the projective nature of XCA causes the loss of 3D structural information, which ...
Improvement in Image Quality and Visibility of Coronary Arteries, Stents, and Valve Structures on CT Angiography by Deep Learning Reconstruction.
Korean journal of radiology
Sep 29, 2022
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
Sep 5, 2022
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...
Deep learning reconstruction allows for usage of contrast agent of lower concentration for coronary CTA than filtered back projection and hybrid iterative reconstruction.
Acta radiologica (Stockholm, Sweden : 1987)
Aug 17, 2022
BACKGROUND: The demand for homogeneous and higher vascular contrast enhancement is critical to provide an appropriate interpretation of abnormal vascular findings in coronary computed tomography angiography (CTA).
Coronary Artery Stent Evaluation by CTA: Impact of Deep Learning Reconstruction and Subtraction Technique.
AJR. American journal of roentgenology
Aug 10, 2022
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
Jul 21, 2022
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
Jul 11, 2022
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
Jul 8, 2022
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...
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