Joint correction of attenuation and scatter in image space using deep convolutional neural networks for dedicated brain 18F-FDG PET.

ABSTRACT: Dedicated brain positron emission tomography (PET) devices can provide higher-resolution images with much lower doses compared to conventional whole-body PET systems, which is important to support PET neuroimaging and particularly useful for the diagnosis of neurodegenerative diseases. However, when a dedicated brain PET scanner does not come with a combined CT or transmission source, there is no direct solution for accurate attenuation and scatter correction, both of which are critical for quantitative PET. To address this problem, we propose joint attenuation and scatter correction (ASC) in image space for non-corrected PET (PETNC) using deep convolutional neural networks (DCNNs). This approach is a one-step process, distinct from conventional methods that rely on generating attenuation

SUBMITTER: Yang J 

PROVIDER: S-EPMC6449185 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature