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Research ArticleCLINICAL INVESTIGATIONS

Automated Quality Control for Segmentation of Myocardial Perfusion SPECT

Yuan Xu, Paul Kavanagh, Mathews Fish, James Gerlach, Amit Ramesh, Mark Lemley, Sean Hayes, Daniel S. Berman, Guido Germano and Piotr J. Slomka
Journal of Nuclear Medicine September 2009, 50 (9) 1418-1426; DOI: https://doi.org/10.2967/jnumed.108.061333
Yuan Xu
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Paul Kavanagh
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Mathews Fish
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James Gerlach
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Amit Ramesh
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Mark Lemley
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Sean Hayes
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Daniel S. Berman
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Guido Germano
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Piotr J. Slomka
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Article Information

vol. 50 no. 9 1418-1426
DOI 
https://doi.org/10.2967/jnumed.108.061333
PubMed 
19690019

Published By 
Society of Nuclear Medicine
Print ISSN 
0161-5505
Online ISSN 
2159-662X
History 
  • Received for publication December 18, 2008
  • Accepted for publication June 9, 2009
  • Published online August 27, 2009.

Article Versions

  • previous version (August 18, 2009 - 05:49).
  • You are viewing the most recent version of this article.
Copyright & Usage 
© 2009 by Society of Nuclear Medicine

Author Information

  1. Yuan Xu 1 ,
  2. Paul Kavanagh 1 ,
  3. Mathews Fish 2 ,
  4. James Gerlach 1 ,
  5. Amit Ramesh 1 ,
  6. Mark Lemley 2 ,
  7. Sean Hayes 1 ,
  8. Daniel S. Berman 1 , 3 ,
  9. Guido Germano 1 , 3 and
  10. Piotr J. Slomka 1 , 3
  1. 1Departments of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, California; 2Sacred Heart Medical Center, Eugene, Oregon; 3David Geffen School of Medicine, UCLA, Los Angeles, California
  1. For correspondence or reprints contact: Piotr J. Slomka, Cedars-Sinai Medical Center, 8700 Beverly Blvd., Taper #A047, Los Angeles, CA 90048. E-mail: piotr.slomka{at}cshs.org
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Cited By...

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  • 48 Citations
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  • Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT
    Julian Betancur, Frederic Commandeur, Mahsaw Motlagh, Tali Sharir, Andrew J. Einstein, Sabahat Bokhari, Mathews B. Fish, Terrence D. Ruddy, Philipp Kaufmann, Albert J. Sinusas, Edward J. Miller, Timothy M. Bateman, Sharmila Dorbala, Marcelo Di Carli, Guido Germano, Yuka Otaki, Balaji K. Tamarappoo, Damini Dey, Daniel S. Berman, Piotr J. Slomka
    JACC: Cardiovascular Imaging 2018 11 11
  • Improved accuracy of myocardial perfusion SPECT for detection of coronary artery disease by machine learning in a large population
    Reza Arsanjani, Yuan Xu, Damini Dey, Vishal Vahistha, Aryeh Shalev, Rine Nakanishi, Sean Hayes, Mathews Fish, Daniel Berman, Guido Germano, Piotr J. Slomka
    Journal of Nuclear Cardiology 2013 20 4
  • Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter Study
    Julian Betancur, Lien-Hsin Hu, Frederic Commandeur, Tali Sharir, Andrew J. Einstein, Mathews B. Fish, Terrence D. Ruddy, Philipp A. Kaufmann, Albert J. Sinusas, Edward J. Miller, Timothy M. Bateman, Sharmila Dorbala, Marcelo Di Carli, Guido Germano, Yuka Otaki, Joanna X. Liang, Balaji K. Tamarappoo, Damini Dey, Daniel S. Berman, Piotr J. Slomka
    Journal of Nuclear Medicine 2019 60 5
  • Comparison of Fully Automated Computer Analysis and Visual Scoring for Detection of Coronary Artery Disease from Myocardial Perfusion SPECT in a Large Population
    Reza Arsanjani, Yuan Xu, Sean W. Hayes, Mathews Fish, Mark Lemley, James Gerlach, Sharmila Dorbala, Daniel S. Berman, Guido Germano, Piotr Slomka
    Journal of Nuclear Medicine 2013 54 2
  • Cardiac imaging: working towards fully-automated machine analysis & interpretation
    Piotr J Slomka, Damini Dey, Arkadiusz Sitek, Manish Motwani, Daniel S Berman, Guido Germano
    Expert Review of Medical Devices 2017 14 3
  • Rationale and design of the REgistry of Fast Myocardial Perfusion Imaging with NExt generation SPECT (REFINE SPECT)
    Piotr J. Slomka, Julian Betancur, Joanna X. Liang, Yuka Otaki, Lien-Hsin Hu, Tali Sharir, Sharmila Dorbala, Marcelo Di Carli, Mathews B. Fish, Terrence D. Ruddy, Timothy M. Bateman, Andrew J. Einstein, Philipp A. Kaufmann, Edward J. Miller, Albert J. Sinusas, Peyman N. Azadani, Heidi Gransar, Balaji K. Tamarappoo, Damini Dey, Daniel S. Berman, Guido Germano
    Journal of Nuclear Cardiology 2020 27 3
  • Automatic and visual reproducibility of perfusion and function measures for myocardial perfusion SPECT
    Yuan Xu, Sean Hayes, Iftikhar Ali, Terrence D. Ruddy, R.Glenn Wells, Daniel S. Berman, Guido Germano, Piotr J. Slomka
    Journal of Nuclear Cardiology 2010 17 6
  • A learning-based automatic segmentation and quantification method on left ventricle in gated myocardial perfusion SPECT imaging: A feasibility study
    Tonghe Wang, Yang Lei, Haipeng Tang, Zhuo He, Richard Castillo, Cheng Wang, Dianfu Li, Kristin Higgins, Tian Liu, Walter J. Curran, Weihua Zhou, Xiaofeng Yang
    Journal of Nuclear Cardiology 2020 27 3
  • Automatic Valve Plane Localization in Myocardial Perfusion SPECT/CT by Machine Learning: Anatomic and Clinical Validation
    Julian Betancur, Mathieu Rubeaux, Tobias A. Fuchs, Yuka Otaki, Yoav Arnson, Leandro Slipczuk, Dominik C. Benz, Guido Germano, Damini Dey, Chih-Jen Lin, Daniel S. Berman, Philipp A. Kaufmann, Piotr J. Slomka
    Journal of Nuclear Medicine 2017 58 6
  • Quantitative analysis of perfusion studies: Strengths and pitfalls
    Piotr Slomka, Yuan Xu, Daniel Berman, Guido Germano
    Journal of Nuclear Cardiology 2012 19 2

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Journal of Nuclear Medicine: 50 (9)
Journal of Nuclear Medicine
Vol. 50, Issue 9
September 2009
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Automated Quality Control for Segmentation of Myocardial Perfusion SPECT
Yuan Xu, Paul Kavanagh, Mathews Fish, James Gerlach, Amit Ramesh, Mark Lemley, Sean Hayes, Daniel S. Berman, Guido Germano, Piotr J. Slomka
Journal of Nuclear Medicine Sep 2009, 50 (9) 1418-1426; DOI: 10.2967/jnumed.108.061333

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Automated Quality Control for Segmentation of Myocardial Perfusion SPECT
Yuan Xu, Paul Kavanagh, Mathews Fish, James Gerlach, Amit Ramesh, Mark Lemley, Sean Hayes, Daniel S. Berman, Guido Germano, Piotr J. Slomka
Journal of Nuclear Medicine Sep 2009, 50 (9) 1418-1426; DOI: 10.2967/jnumed.108.061333
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Cited By...

  • Quantitative Clinical Nuclear Cardiology, Part 1: Established Applications
  • Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter Study
  • Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT: A Multicenter Study
  • Automatic Valve Plane Localization in Myocardial Perfusion SPECT/CT by Machine Learning: Anatomic and Clinical Validation
  • Comparison of Fully Automated Computer Analysis and Visual Scoring for Detection of Coronary Artery Disease from Myocardial Perfusion SPECT in a Large Population
  • Google Scholar

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