NDLI: Region-based maximum likelihood reconstruction in positron emission tomography for quantitative oncological analysis

Content Provider	IEEE Xplore Digital Library
Author	Bernardi, E.D. Faggiano, E. Zito, F. Baselli, G.
Copyright Year	2008
Description	Author affiliation: Bioengineering Department, Politecnico di Milano, Milan, Italy (Bernardi, E.D.; Faggiano, E.; Baselli, G.) \|\| Nuclear Medicine Department, Ospedale Maggiore Policlinico, Mangiagalli e Regina Elena, Milan, Italy (Zito, F.)
Abstract	We propose a maximum likelihood (ML) reconstruction strategy for the quantification of uptake and volume of oncological lesions in Positron Emission Tomography. The ML is applied on volumetric regional basis functions identified on smooth standard clinical images (STD-CI). The lesion to be quantified is segmented with a k-means algorithm in three areas to take into account and recover the blurring introduced by the scanner Point Spread Function (PSF) and by the algorithm used to obtain STD-CI. For each of the three areas, a constant regional basis function initialized to the average inside the area is defined. The volume outside the lesion is handled as an unique basis function initialized to the activity spatial distribution estimated by STD-CI and is "frozen" in the reconstruction process except for a gain coefficient. The coefficients of the regional basis functions are iteratively estimated with an AWOSEM algorithm containing a 3D anisotropic and spatially variant model of the scanner PSF. The process of segmentation-reconstruction is iterated until the lesion segmentation converges. At each iteration the reconstructed volume is locally filtered with the scanner PSF before the segmentation step. We report results obtained on sphere phantom studies with activity contrasts of 7.5 and 4. The improvement in quantification obtained is remarkable thanks to the recovery of the scanner blur and to the possibility to locally better approach the maximum likelihood solution. The strategy appears also able to provide a reliable quantification of volume.
Starting Page	1
Ending Page	4
File Size	267457
Page Count	4
File Format	PDF
ISBN	9781424427147
ISSN	10957863
DOI	10.1109/NSSMIC.2008.4804130
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 Image reconstruction Lesions Maximum likelihood estimation Iterative algorithms Maximum likelihood detection Noise level Image segmentation Convergence Noise reduction
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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