NDLI: Dynamic GMRF priors for MAP reconstructions

Content Provider	IEEE Xplore Digital Library
Author	Yuxiang Xing Kejun Kang Hongbing Lu Li Zhang
Copyright Year	2004
Description	Author affiliation: Dept. of Eng. Phys., Tsinghua Univ., Beijing, China (Yuxiang Xing; Kejun Kang)
Abstract	The maximum a posteriori method has been intensively studied in the literature of tomographic reconstructions, especially in the noisy emission computer tomography. It is well acknowledged that the quality of reconstructed images from MAP could be improved by a carefully chosen prior. The prior not only improve the condition number of the optimization problem, but also couple in information about the object being imaged. Here, we propose a new dynamic Gaussian Markov Random Field (GMRF) prior extended from a Membrane prior. The dynamic GMRF prior provides adaptive penalty scheme according to signal magnitude. It could be realized with little extra computational load compared to a Membrane prior, but could supply more flexible and better performance than the membrane prior. The idea is generalizable to other priors. We compare the performance of MAP reconstructions by simulations with an Membrane prior favoring uniform smoothness and with this new dynamic GMRF prior favoring nonuniform smoothness that correlates with signal magnitudes by simulations. Our results show that the dynamic GMRF prior exhibits improved resolution and contrast for high value region and visually improves the lesion-detectability.
Starting Page	3974
Ending Page	3977
File Size	725156
Page Count	4
File Format	PDF
ISBN	0780387007
ISSN	10823654
e-ISBN	0780387015
DOI	10.1109/NSSMIC.2004.1466748
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-10-16
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image reconstruction Biomembranes Markov random fields Physics Military computing Tomography Reconstruction algorithms Biomedical engineering Computer applications Biomedical imaging
Content Type	Text
Resource Type	Article

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