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Research ArticleBasic Science Investigation

Deep Learning–Based Attenuation Correction Improves Diagnostic Accuracy of Cardiac SPECT

Aakash D. Shanbhag, Robert J.H. Miller, Konrad Pieszko, Mark Lemley, Paul Kavanagh, Attila Feher, Edward J. Miller, Albert J. Sinusas, Philipp A. Kaufmann, Donghee Han, Cathleen Huang, Joanna X. Liang, Daniel S. Berman, Damini Dey and Piotr J. Slomka
Journal of Nuclear Medicine March 2023, 64 (3) 472-478; DOI: https://doi.org/10.2967/jnumed.122.264429
Aakash D. Shanbhag
1Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars–Sinai Medical Center, Los Angeles, California;
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Robert J.H. Miller
2Department of Cardiac Sciences, University of Calgary, Calgary, Alberta, Canada;
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Konrad Pieszko
3Department of Interventional Cardiology and Cardiac Surgery, University of Zielona Góra, Zielona Góra, Poland;
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Mark Lemley
1Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars–Sinai Medical Center, Los Angeles, California;
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Paul Kavanagh
1Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars–Sinai Medical Center, Los Angeles, California;
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Attila Feher
4Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut; and
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Edward J. Miller
4Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut; and
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Albert J. Sinusas
4Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut; and
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Philipp A. Kaufmann
5Cardiac Imaging, Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
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Donghee Han
1Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars–Sinai Medical Center, Los Angeles, California;
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Cathleen Huang
1Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars–Sinai Medical Center, Los Angeles, California;
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Joanna X. Liang
1Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars–Sinai Medical Center, Los Angeles, California;
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Daniel S. Berman
1Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars–Sinai Medical Center, Los Angeles, California;
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Damini Dey
1Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars–Sinai Medical Center, Los Angeles, California;
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Piotr J. Slomka
1Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars–Sinai Medical Center, Los Angeles, California;
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Article Information

vol. 64 no. 3 472-478
DOI 
https://doi.org/10.2967/jnumed.122.264429
PubMed 
36137759

Published By 
Society of Nuclear Medicine
Print ISSN 
0161-5505
Online ISSN 
2159-662X
History 
  • Received for publication June 21, 2022
  • Revision received September 16, 2022
  • Published online March 2, 2023.

Article Versions

  • previous version (September 22, 2022 - 12:25).
  • You are viewing the most recent version of this article.
Copyright & Usage 
© 2023 by the Society of Nuclear Medicine and Molecular Imaging.

Author Information

  1. Aakash D. Shanbhag*,1,
  2. Robert J.H. Miller*,2,
  3. Konrad Pieszko3,
  4. Mark Lemley1,
  5. Paul Kavanagh1,
  6. Attila Feher4,
  7. Edward J. Miller4,
  8. Albert J. Sinusas4,
  9. Philipp A. Kaufmann5,
  10. Donghee Han1,
  11. Cathleen Huang1,
  12. Joanna X. Liang1,
  13. Daniel S. Berman1,
  14. Damini Dey1 and
  15. Piotr J. Slomka1
  1. 1Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, and Biomedical Sciences, Cedars–Sinai Medical Center, Los Angeles, California;
  2. 2Department of Cardiac Sciences, University of Calgary, Calgary, Alberta, Canada;
  3. 3Department of Interventional Cardiology and Cardiac Surgery, University of Zielona Góra, Zielona Góra, Poland;
  4. 4Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut; and
  5. 5Cardiac Imaging, Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
  1. For correspondence or reprints, contact Piotr J. Slomka (piotr.slomka{at}cshs.org).
  1. ↵* Contributed equally to this work.

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Deep Learning–Based Attenuation Correction Improves Diagnostic Accuracy of Cardiac SPECT
Aakash D. Shanbhag, Robert J.H. Miller, Konrad Pieszko, Mark Lemley, Paul Kavanagh, Attila Feher, Edward J. Miller, Albert J. Sinusas, Philipp A. Kaufmann, Donghee Han, Cathleen Huang, Joanna X. Liang, Daniel S. Berman, Damini Dey, Piotr J. Slomka
Journal of Nuclear Medicine Mar 2023, 64 (3) 472-478; DOI: 10.2967/jnumed.122.264429

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Deep Learning–Based Attenuation Correction Improves Diagnostic Accuracy of Cardiac SPECT
Aakash D. Shanbhag, Robert J.H. Miller, Konrad Pieszko, Mark Lemley, Paul Kavanagh, Attila Feher, Edward J. Miller, Albert J. Sinusas, Philipp A. Kaufmann, Donghee Han, Cathleen Huang, Joanna X. Liang, Daniel S. Berman, Damini Dey, Piotr J. Slomka
Journal of Nuclear Medicine Mar 2023, 64 (3) 472-478; DOI: 10.2967/jnumed.122.264429
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Keywords

  • attenuation correction
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  • deep learning
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