AIMC Topic: Myocardial Perfusion Imaging
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The prognostic value of automated coronary calcium derived by a deep learning approach on non-ECG gated CT images from Rb-PET/CT myocardial perfusion imaging.
International journal of cardiology
Jan 4, 2021
BACKGROUND: Assessment of both coronary artery calcium(CAC) scores and myocardial perfusion imaging(MPI) in patients suspected of coronary artery disease(CAD) provides incremental prognostic information. We used an automated method to determine CAC s...
Deep learning with noise-to-noise training for denoising in SPECT myocardial perfusion imaging.
Medical physics
Nov 23, 2020
PURPOSE: Post-reconstruction filtering is often applied for noise suppression due to limited data counts in myocardial perfusion imaging (MPI) with single-photon emission computed tomography (SPECT). We study a deep learning (DL) approach for denoisi...
[Artificial intelligence, of course!].
Annales de cardiologie et d'angeiologie
Oct 7, 2020
Functional cardiac CT-Going beyond Anatomical Evaluation of Coronary Artery Disease with Cine CT, CT-FFR, CT Perfusion and Machine Learning.
The British journal of radiology
Aug 12, 2020
The aim of this review is to provide an overview of different functional cardiac CT techniques which can be used to supplement assessment of the coronary arteries to establish the significance of coronary artery stenoses. We focus on cine-CT, CT-FFR,...
Automatic characterization of myocardial perfusion imaging polar maps employing deep learning and data augmentation.
Hellenic journal of nuclear medicine
Jul 27, 2020
OBJECTIVE: To investigate a deep learning technique, more specifically state-of-the-art convolutional neural networks (CNN), for automatic characterization of polar maps derived from myocardial perfusion imaging (MPI) studies for the diagnosis of cor...
Improved myocardial perfusion PET imaging using artificial neural networks.
Physics in medicine and biology
Jul 20, 2020
Myocardial perfusion (MP) PET imaging plays a key role in risk assessment and stratification of patients with coronary artery disease. In this work, we proposed a patch-based artificial neural network (ANN) fusion approach that integrates information...
Deep learning, another important tool for improving acquisition efficiency in SPECT MPI Imaging.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
May 17, 2020
Standard SPECT myocardial perfusion estimation from half-time acquisitions using deep convolutional residual neural networks.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Apr 28, 2020
INTRODUCTION: The purpose of this work was to assess the feasibility of acquisition time reduction in MPI-SPECT imaging using deep leering techniques through two main approaches, namely reduction of the acquisition time per projection and reduction o...
Global Developments in Stress Perfusion Cardiovascular Magnetic Resonance.
Circulation
Apr 20, 2020
The Prognostic Significance of Quantitative Myocardial Perfusion: An Artificial Intelligence-Based Approach Using Perfusion Mapping.
Circulation
Feb 14, 2020
BACKGROUND: Myocardial perfusion reflects the macro- and microvascular coronary circulation. Recent quantitation developments using cardiovascular magnetic resonance perfusion permit automated measurement clinically. We explored the prognostic signif...
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