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Entropy Maximization Algorithm for Positron Emission Tomography

Mondal, Partha Pratim and Rajan, K (2002) Entropy Maximization Algorithm for Positron Emission Tomography. In: 9th International Conference on Neural Information Processing, 2002. ICONIP '02, 18-22 November, Singapore, Vol.1, 222-225.


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The expectation maximization (EM) algorithm is extensively used for tomographic image reconstruction based on positron emission tomography (PET) modality. The EM algorithm gives good reconstructed images compared to those created by deterministic methods such as filtered back projection (FBP) and convolution back projection (CBP). However, the computational complexity of EM-based algorithm is high due to the iterative nature of the algorithm. Prior knowledge of the estimate has been added to the basic EM algorithm to improve image quality as well as to reduce the number of iterations required for an acceptable image quality. We have developed an algorithm which produces better quality images in much lesser number of iterations, thereby speeding up the image reconstruction task.

Item Type: Conference Paper
Additional Information: Copyright 1990 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: Entropy maximization;Poisson process;Conditional probability;Conditional entropy
Department/Centre: Division of Physical & Mathematical Sciences > Physics
Depositing User: HS Usha
Date Deposited: 19 Jan 2006
Last Modified: 19 Sep 2010 04:23
URI: http://eprints.iisc.ac.in/id/eprint/5154

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