Deep learning-guided estimation of attenuation correction factors from time-of-flight PET emission data.
Journal:
Medical image analysis
Published Date:
May 19, 2020
Abstract
PURPOSE: 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.