NDLI: Investigation of observer-performance in MAP-EM reconstruction with anatomical priors and scatter correction for lesion detection in /sup 67/Ga images

Content Provider	IEEE Xplore Digital Library
Author	Bruyant, P.P. Gifford, H.C. Gindi, G. King, M.A.
Copyright Year	2004
Description	Author affiliation: Massachusetts Univ., Worcester, MA, USA (Bruyant, P.P.; Gifford, H.C.)
Abstract	In a previous work, we showed that anatomical priors can improve lesion detection in simulated Ga67 images of the chest. We herein expand and enhance our previous investigations by adding scatter in the projections, by using the triple energy window scatter compensation method and by implementing a new scheme for image reconstruction. Phantom images are created using the SIMIND Monte Carlo simulation software and the mathematical cardiac-torso (MCAT) phantom. The anatomical data are the original, noise-free slices of the MCAT phantom. Images are reconstructed using the DePierro algorithm. Two weights for the prior are tested (0.005 and 0.02). The following reconstruction scheme is used to reach convergence: The 120 projections are reconstructed successively with 4, 8, 24, 60, and 120 projections per subset with 1,1,1,1, and 50 iterations respectively; the result of each reconstruction is used as an initial estimate for the next reconstruction. Several strategies were investigated: no anatomical prior information, and anatomical information for organs and/or lesion. Lesion detection was performed by a numerical observer with an LROC task. Strategies including anatomical priors yield better results in terms of lesion detection, as compared to the strategy using no prior and only post-reconstruction Gaussian smoothing.
Starting Page	3166
Ending Page	3169
File Size	456347
Page Count	4
File Format	PDF
ISBN	0780382579
ISSN	10823654
DOI	10.1109/NSSMIC.2003.1352568
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-10-19
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image reconstruction Lesions Electromagnetic scattering Particle scattering Imaging phantoms Neoplasms Convergence Iterative algorithms Testing Smoothing methods
Content Type	Text
Resource Type	Article

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