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Scientific article
English

Deep learning-guided estimation of attenuation correction factors from time-of-flight PET emission data

Published inMedical Image Analysis, vol. 64, 101718
Publication date2020
Abstract

Attenuation correction (AC) is essential for quantitative PET imaging. In the absence of concurrent CT scanning, for instance on hybrid PET/MRI systems or dedicated brain PET scanners, an accurate approach for synthetic CT generation is highly desired. In this work, a novel framework is proposed wherein attenuation correction factors (ACF) are estimated from time-of-flight (TOF) PET emission data using deep learning.

Keywords
  • PET/CT
  • Attenuation correction
  • Machine learning
  • Deep learning
  • Quantification
Citation (ISO format)
ARABI, Hossein, ZAIDI, Habib. Deep learning-guided estimation of attenuation correction factors from time-of-flight PET emission data. In: Medical Image Analysis, 2020, vol. 64, p. 101718. doi: 10.1016/j.media.2020.101718
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Identifiers
ISSN of the journal1361-8415
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Technical informations

Creation05/31/2020 5:17:00 PM
First validation05/31/2020 5:17:00 PM
Update time03/15/2023 10:05:03 PM
Status update03/15/2023 10:05:01 PM
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