AIMC Topic: Coronary Artery Disease
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Deep learning prediction of quantitative coronary angiography values using myocardial perfusion images with a CZT camera.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
May 24, 2022
PURPOSE: Evaluate the prediction of quantitative coronary angiography (QCA) values from MPI, by means of deep learning.
Safety and Efficacy of Robotic-Assisted PCI.
Current cardiology reports
May 19, 2022
PURPOSE OF REVIEW: Robotics has been used in multiple areas of procedural medical intervention. Robotic percutaneous coronary intervention (PCI) has been available since 2004. Its adoption has been slow with initial application in simple cases.
What have we learned from robotic-percutaneous coronary intervention so far? Early experience in a tertiary center.
Revista espanola de cardiologia (English ed.)
May 12, 2022
Deep learning-based atherosclerotic coronary plaque segmentation on coronary CT angiography.
European radiology
May 7, 2022
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...
Explainable Deep Learning Improves Physician Interpretation of Myocardial Perfusion Imaging.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
May 5, 2022
Artificial intelligence may improve accuracy of myocardial perfusion imaging (MPI) but will likely be implemented as an aid to physician interpretation rather than an autonomous tool. Deep learning (DL) has high standalone diagnostic accuracy for obs...
Automatic coronary artery segmentation and diagnosis of stenosis by deep learning based on computed tomographic coronary angiography.
European radiology
Apr 8, 2022
OBJECTIVES: Coronary computed tomography angiography (CCTA) has rapidly developed in the coronary artery disease (CAD) field. However, manual coronary artery tree segmentation and reconstruction are time-consuming and tedious. Deep learning algorithm...
Application of a deep learning algorithm to calcium scoring in myocardial perfusion imaging.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Mar 30, 2022
Improving convolutional neural network learning based on a hierarchical bezier generative model for stenosis detection in X-ray images.
Computer methods and programs in biomedicine
Mar 23, 2022
BACKGROUND AND OBJECTIVE: Automatic detection of stenosis on X-ray Coronary Angiography (XCA) images may help diagnose early coronary artery disease. Stenosis is manifested by a buildup of plaque in the arteries, decreasing the blood flow to the hear...
"Virtual" attenuation correction: improving stress myocardial perfusion SPECT imaging using deep learning.
European journal of nuclear medicine and molecular imaging
Mar 21, 2022
PURPOSE: Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) is widely used for coronary artery disease (CAD) evaluation. Although attenuation correction is recommended to diminish image artifacts and improve d...
Fully automated deep learning powered calcium scoring in patients undergoing myocardial perfusion imaging.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Mar 17, 2022
BACKGROUND: To assess the accuracy of fully automated deep learning (DL) based coronary artery calcium scoring (CACS) from non-contrast computed tomography (CT) as acquired for attenuation correction (AC) of cardiac single-photon-emission computed to...
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