Development of transfer learning datasets using realistic simulation of myocardial perfusion SPECT images for a deep learning model
404 Objectives: The goal is to develop an effective transfer learning (TL) dataset using
realistic simulation techniques for the highest possible performance of a deep learning (DL) …
realistic simulation techniques for the highest possible performance of a deep learning (DL) …
Automatic Deep Learning Analysis of Upright-Supine High-Speed SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A …
507 Objectives: Combined analysis of SPECT myocardial perfusion imaging (MPI)
performed on patients lying upright and supine had demonstrated improved diagnostic …
performed on patients lying upright and supine had demonstrated improved diagnostic …
[PDF][PDF] Transfer Learning for Disease Diagnosis from Myocardial Perfusion SPECT Imaging.
PN Hai, NC Thanh, NT Trung… - Computers, Materials & …, 2022 - researchgate.net
Coronary artery disease (CAD) is one of the most common pathological conditions and the
major global cause of death. Myocardial perfusion imaging (MPI) using single-photon …
major global cause of death. Myocardial perfusion imaging (MPI) using single-photon …
Deep learning for prediction of obstructive disease from fast myocardial perfusion SPECT: a multicenter study
J Betancur, F Commandeur, M Motlagh, T Sharir… - JACC: Cardiovascular …, 2018 - jacc.org
Objectives: The study evaluated the automatic prediction of obstructive disease from
myocardial perfusion imaging (MPI) by deep learning as compared with total perfusion …
myocardial perfusion imaging (MPI) by deep learning as compared with total perfusion …
Deep learning analysis of upright-supine high-efficiency SPECT myocardial perfusion imaging for prediction of obstructive coronary artery disease: a multicenter study
J Betancur, LH Hu, F Commandeur… - Journal of Nuclear …, 2019 - Soc Nuclear Med
Combined analysis of SPECT myocardial perfusion imaging (MPI) performed with a solid-
state camera on patients in 2 positions (semiupright, supine) is routinely used to mitigate …
state camera on patients in 2 positions (semiupright, supine) is routinely used to mitigate …
Prediction of revascularization after myocardial perfusion SPECT by machine learning in a large population
Objective We aimed to investigate if early revascularization in patients with suspected
coronary artery disease can be effectively predicted by integrating clinical data and …
coronary artery disease can be effectively predicted by integrating clinical data and …
[HTML][HTML] An explainable classification method of SPECT myocardial perfusion images in nuclear cardiology using deep learning and grad-CAM
Background: This study targets the development of an explainable deep learning
methodology for the automatic classification of coronary artery disease, utilizing SPECT MPI …
methodology for the automatic classification of coronary artery disease, utilizing SPECT MPI …
Deep learning analysis of Tl-201 myocardial perfusion imaging for improve diagnostic accuracy
CH Chiu, CY Cheng, TW Tseng, YP Yin - 2019 - Soc Nuclear Med
169 Objectives: Tl-201 myocardial perfusion imaging (MPI) is widely used to diagnose
coronary artery disease (CAD). Deep learning (DL) would improve diagnostic accuracy of …
coronary artery disease (CAD). Deep learning (DL) would improve diagnostic accuracy of …
Machine learning models for PET myocardial perfusion imaging
MC Williams - Journal of Nuclear Cardiology, 2024 - research.ed.ac.uk
Machine learning has the potential to improve patient care by automating the assessment of
medical imaging. Machine learning models have been developed to identify ischaemia and …
medical imaging. Machine learning models have been developed to identify ischaemia and …
[HTML][HTML] Deep learning: Opening a third eye to myocardial perfusion imaging
Deep learning (DL) methods are increasingly used in both research and practice of
medicine for acquisition, segmentation, analysis, and interpretation of medical imaging …
medicine for acquisition, segmentation, analysis, and interpretation of medical imaging …
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