Meeting ReportPhysics, Instrumentation & Data Sciences - Data Sciences
AI-based Cardiac Resynchronization Therapy Response Evaluation Using Quantitative SPECT Features
Maziar Sabouri, Omid Gharibi, Ghasem Hajianfar, Zahra Hosseini, Zahra Akbari Khanaposhtani, Fereshteh Yousefirizi, Ahmad Bitarafan Rajabi, Habib Zaidi, Isaac Shiri and Arman Rahmim
Journal of Nuclear Medicine June 2024, 65 (supplement 2) 242326;
Maziar Sabouri
1Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
Omid Gharibi
2Department of Medical Physics, Iran University of Medical Sciences, Tehran, Iran
Ghasem Hajianfar
3Division of Nuclear medicine and Molecular Imaging, Geneva University Hospital
Zahra Hosseini
4Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Science, Tehran, Iran
Zahra Akbari Khanaposhtani
Fereshteh Yousefirizi
5BCCRC/UBC
Ahmad Bitarafan Rajabi
6Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Science
Habib Zaidi
7Geneva University Hospital
Isaac Shiri
Arman Rahmim
8University of British Columbia
In this issue
Journal of Nuclear Medicine
Vol. 65, Issue supplement 2
June 1, 2024
AI-based Cardiac Resynchronization Therapy Response Evaluation Using Quantitative SPECT Features
Maziar Sabouri, Omid Gharibi, Ghasem Hajianfar, Zahra Hosseini, Zahra Akbari Khanaposhtani, Fereshteh Yousefirizi, Ahmad Bitarafan Rajabi, Habib Zaidi, Isaac Shiri, Arman Rahmim
Journal of Nuclear Medicine Jun 2024, 65 (supplement 2) 242326;
AI-based Cardiac Resynchronization Therapy Response Evaluation Using Quantitative SPECT Features
Maziar Sabouri, Omid Gharibi, Ghasem Hajianfar, Zahra Hosseini, Zahra Akbari Khanaposhtani, Fereshteh Yousefirizi, Ahmad Bitarafan Rajabi, Habib Zaidi, Isaac Shiri, Arman Rahmim
Journal of Nuclear Medicine Jun 2024, 65 (supplement 2) 242326;
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