NDLI: Fast and accurate PET preclinical data analysis: Segmentation and Partial Volume Effect correction with no anatomical priors

Content Provider	IEEE Xplore Digital Library
Author	Maroy, Renaud Viel, Thomas Boisgard, Raphael Comtat, Claude Trebossen, Regine Tavitian, Bertrand
Copyright Year	2008
Description	Author affiliation: Commissariat à l¿Energie Atomique, Orsay, 91401, France (Maroy, Renaud; Viel, Thomas; Boisgard, Raphael; Comtat, Claude; Trebossen, Regine; Tavitian, Bertrand)
Abstract	The Partial Volume Effect hampers the quantification of rodent dynamic PET images. The work proposes a whole process for TAC extraction from the PET images without anatomical information requirement. The PET images were segmented using the Local Means Analysis segmentation method, and the resulting regions were used as spatial domains for a Geometric Transfer Matrix based method. The TAC estimation was assessed on phantom simulations and experimental datasets with ex-vivo measurements, and compared to reference methods: the mean TAC computation method the original Geometric Transfer Matrix method. Our GTM based TAC estimation method performed better than the GTM method and the mean TAC computation in terms of correlation of the estimated TACs with the true ones, of contrast recovery and error.
Starting Page	5498
Ending Page	5501
File Size	9646741
Page Count	4
File Format	PDF
ISBN	9781424427147
ISSN	10957863
DOI	10.1109/NSSMIC.2008.4774497
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-19
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Positron emission tomography Data analysis Image segmentation Imaging phantoms Mice Rodents Helium Nuclear and plasma sciences Data mining Image analysis
Content Type	Text
Resource Type	Article

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