AIMC Topic: Myocardial Perfusion Imaging
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Automatic reorientation by deep learning to generate short-axis SPECT myocardial perfusion images.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Mar 1, 2023
BACKGROUND: Single photon emission computed tomography (SPECT) myocardial perfusion images (MPI) can be displayed both in traditional short-axis (SA) cardiac planes and polar maps for interpretation and quantification. It is essential to reorient the...
A deep learning-based fully automatic and clinical-ready framework for regional myocardial segmentation and myocardial ischemia evaluation.
Medical & biological engineering & computing
Feb 11, 2023
Myocardial ischemia diagnosis with CT perfusion imaging (CTP) is important in coronary artery disease management. Traditional analysis procedure is time-consuming and error-prone due to the semi-manual and operator-dependent nature. To improve the di...
Multi-center, multi-vendor validation of deep learning-based attenuation correction in SPECT MPI: data from the international flurpiridaz-301 trial.
European journal of nuclear medicine and molecular imaging
Nov 19, 2022
PURPOSE: Although SPECT myocardial perfusion imaging (MPI) is susceptible to artifacts from soft tissue attenuation, most scans are performed without attenuation correction. Deep learning-based attenuation corrected (DLAC) polar maps improved diagnos...
AI-based classification algorithms in SPECT myocardial perfusion imaging for cardiovascular diagnosis: a review.
Nuclear medicine communications
Nov 15, 2022
In the last few years, deep learning has made a breakthrough and established its position in machine learning classification problems in medical image analysis. Deep learning has recently displayed remarkable applicability in a range of different med...
Deep learning for myocardial ischemia auxiliary diagnosis using CZT SPECT myocardial perfusion imaging.
Journal of the Chinese Medical Association : JCMA
Oct 28, 2022
BACKGROUND: The World Health Organization reported that cardiovascular disease is the most common cause of death worldwide. On average, one person dies of heart disease every 26 min worldwide. Deep learning approaches are characterized by the appropr...
Direct Risk Assessment From Myocardial Perfusion Imaging Using Explainable Deep Learning.
JACC. Cardiovascular imaging
Oct 19, 2022
BACKGROUND: Myocardial perfusion imaging (MPI) is frequently used to provide risk stratification, but methods to improve the accuracy of these predictions are needed.
Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images.
European journal of nuclear medicine and molecular imaging
Oct 4, 2022
PURPOSE: Artificial intelligence (AI) has high diagnostic accuracy for coronary artery disease (CAD) from myocardial perfusion imaging (MPI). However, when trained using high-risk populations (such as patients with correlating invasive testing), the ...
Deep Learning-Based Attenuation Correction Improves Diagnostic Accuracy of Cardiac SPECT.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Sep 22, 2022
To improve diagnostic accuracy, myocardial perfusion imaging (MPI) SPECT studies can use CT-based attenuation correction (AC). However, CT-based AC is not available for most SPECT systems in clinical use, increases radiation exposure, and is impacted...
Deep Learning for Explainable Estimation of Mortality Risk From Myocardial Positron Emission Tomography Images.
Circulation. Cardiovascular imaging
Sep 20, 2022
BACKGROUND: We aim to develop an explainable deep learning (DL) network for the prediction of all-cause mortality directly from positron emission tomography myocardial perfusion imaging flow and perfusion polar map data and evaluate it using prospect...
Polar map-free 3D deep learning algorithm to predict obstructive coronary artery disease with myocardial perfusion CZT-SPECT.
European journal of nuclear medicine and molecular imaging
Sep 14, 2022
PURPOSE: Deep learning (DL) models have been shown to outperform total perfusion deficit (TPD) quantification in predicting obstructive coronary artery disease (CAD) from myocardial perfusion imaging (MPI). However, previously published methods have ...
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