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Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine|May 6, 2005
Automatic detection and size quantification of infarcts by myocardial perfusion SPECT: clinical validation by delayed-enhancement MRIPiotr J Slomka, David Fieno, Louise Thomson, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|March 15, 2017
Fully automated analysis of attenuation-corrected SPECT for the long-term prediction of acute myocardial infarctionManish Motwani, William D Leslie, Andrew L Goertzen, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|January 31, 2014
Clinical value of supine and upright myocardial perfusion imaging in obese patients using the D-SPECT cameraSimona Ben-Haim, Omar Almukhailed, Johanne Neill, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|January 22, 2009
Threshold, incidence, and predictors of prognostically high-risk silent ischemia in asymptomatic patients without prior diagnosis of coronary artery diseaseMichael J Zellweger, Rory Hachamovitch, Xingping Kang, et al.
Journal of Cardiovascular Computed Tomography|April 23, 2011
Interscan reproducibility of computer-aided epicardial and thoracic fat measurement from noncontrast cardiac CTRyo Nakazato, Haim Shmilovich, Balaji K Tamarappoo, et al.
Cardiovascular Pathology : the Official Journal of the Society for Cardiovascular Pathology|June 24, 2004
Scar formation after ischemic myocardial injury in MRL miceYong-Seog Oh, Louise E J Thomson, Michael C Fishbein, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology|February 6, 2007
Combined quantitative supine-prone myocardial perfusion SPECT improves detection of coronary artery disease and normalcy rates in womenPiotr J Slomka, Hidetaka Nishina, Aiden Abidov, et al.
Journal of the American Society of Echocardiography : Official Publication of the American Society of Echocardiography|June 1, 2025
Using Deep Learning to Predict Cardiovascular Magnetic Resonance Findings From Echocardiographic VideosYuki Sahashi, Milos Vukadinovic, Grant Duffy, et al.
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