20 March 2015 Computational analysis of PET by AIBL (CapAIBL): a cloud-based processing pipeline for the quantification of PET images
Author Affiliations +
Abstract
With the advances of PET tracers for β-Amyloid (Aβ) detection in neurodegenerative diseases, automated quantification methods are desirable. For clinical use, there is a great need for PET-only quantification method, as MR images are not always available. In this paper, we validate a previously developed PET-only quantification method against MR-based quantification using 6 tracers: 18F-Florbetaben (N=148), 18F-Florbetapir (N=171), 18F-NAV4694 (N=47), 18F-Flutemetamol (N=180), 11C-PiB (N=381) and 18F-FDG (N=34). The results show an overall mean absolute percentage error of less than 5% for each tracer. The method has been implemented as a remote service called CapAIBL (http://milxcloud.csiro.au/capaibl). PET images are uploaded to a cloud platform where they are spatially normalised to a standard template and quantified. A report containing global as well as local quantification, along with surface projection of the β-Amyloid deposition is automatically generated at the end of the pipeline and emailed to the user.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Pierrick Bourgeat, Vincent Dore, Jurgen Fripp, Victor L. Villemagne, Chris C. Rowe, Olivier Salvado, "Computational analysis of PET by AIBL (CapAIBL): a cloud-based processing pipeline for the quantification of PET images", Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 94132V (20 March 2015); doi: 10.1117/12.2082492; https://doi.org/10.1117/12.2082492
PROCEEDINGS
7 PAGES


SHARE
Back to Top