Hybrid Prior Method for Positron Emission Tomographic Image Reconstruction

Mondal, Partha Pratim and Rajan, K (2004) Hybrid Prior Method for Positron Emission Tomographic Image Reconstruction. In: International Conference on Intelligent Sensing and Information Processing., 4-7 January 2004, Chennai, India, pp. 73-76.

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Abstract

Maximum a-posteriori (MAP) estimation has the advantage of incorporating prior knowledge in the image reconstruction procedure which makes it a superior estimation technique compared to convolution back-projection (CBP), maximum likelihood (ML) etc. The inclusion of prior knowledge greatly improves the image quality. Howevel; ex- cess smoothening occurs as the MAP-iterations are continued. In biomedical imaging sharp reconstruction is oj potential use. To meet these requirements a new prior is proposed which is capable of enhancing the edges by recognizing the correlated neighbors while restoring homogeneity in the uniform regions of the reconstruction. The proposed prior serves as a post-processing technique in Bayesiari domain, once an approxirnate smooth reconstruction is generated by MAP-algorithm. Simulated experiments show improved sharp reconstruction with the proposed post-processing technique.

Item Type:	Conference Paper
Publisher:	IEEE
Additional Information:	©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords:	Bayesian Estimation;Gibbs Prior
Department/Centre:	Division of Physical & Mathematical Sciences > Physics
Date Deposited:	25 Aug 2008
Last Modified:	19 Sep 2010 04:12
URI:	http://eprints.iisc.ac.in/id/eprint/387

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