Fast Reconstruction for Deep Learning PET Head Motion Correction.

ABSTRACT: Head motion correction is an essential component of brain PET imaging, in which even motion of small magnitude can greatly degrade image quality and introduce artifacts. Building upon previous work, we propose a new head motion correction framework taking fast reconstructions as input. The main characteristics of the proposed method are: (i) the adoption of a high-resolution short-frame fast reconstruction workflow; (ii) the development of a novel encoder for PET data representation extraction; and (iii) the implementation of data augmentation techniques. Ablation studies are conducted to assess the individual contributions of each of these design choices. Furthermore, multi-subject studies are conducted on an ¹⁸F-FPEB dataset, and the method performance is qualitatively and qua

SUBMITTER: Zeng T 

PROVIDER: S-EPMC10758999 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature