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

doi:10.2967/jnumed.122.264429

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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Journal of Nuclear Medicine

Vol. 64, Issue 3

March 1, 2023

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

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

Journal of Nuclear Medicine Mar 2023, 64 (3) 472-478; DOI: 10.2967/jnumed.122.264429

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Keywords

attenuation correction
SPECT
myocardial perfusion imaging
deep learning
artificial intelligence

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