AIMC Topic: Myocardial Perfusion Imaging

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Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images.

European journal of nuclear medicine and molecular imaging
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
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
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
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 ...

A method using deep learning to discover new predictors from left-ventricular mechanical dyssynchrony for CRT response.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: Studies have shown that the conventional parameters characterizing left ventricular mechanical dyssynchrony (LVMD) measured on gated SPECT myocardial perfusion imaging (MPI) have their own statistical limitations in predicting cardiac res...

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
PURPOSE: Evaluate the prediction of quantitative coronary angiography (QCA) values from MPI, by means of deep learning.

Deep learning: Opening a third eye to myocardial perfusion imaging.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology

Explainable Deep Learning Improves Physician Interpretation of Myocardial Perfusion Imaging.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
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...