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Proceedings Paper

PET image reconstruction using simulated annealing
Author(s): Erik Sundermann; Ignace L. Lemahieu
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Paper Abstract

In positron emission tomography (PET) images have to be reconstructed from noisy projection data. The noise on the PET data can be modeled by a Poisson distribution. The development of statistical (iterative) reconstruction techniques addresses the problem of noise. In this paper we present the results of introducing the simulated annealing technique as a statistical reconstruction algorithm for PET. We have successfully implemented a reconstruction algorithm based upon simulated annealing, with paying particular attention to the fine-tuning of various parameters (cooling schedule, granularity, stopping rule, ...). In addition, we have developed a cost function more appropriate to the noise statistics (e.g. Poisson) and the reconstruction method (e.g. ML). The comparison with other reconstruction methods using computer phantom studies proves the potential power of the simulated annealing technique for the reconstruction of PET-images.

Paper Details

Date Published: 12 May 1995
PDF: 9 pages
Proc. SPIE 2434, Medical Imaging 1995: Image Processing, (12 May 1995); doi: 10.1117/12.208709
Show Author Affiliations
Erik Sundermann, Univ. of Ghent (Belgium)
Ignace L. Lemahieu, Univ. of Ghent (Belgium)


Published in SPIE Proceedings Vol. 2434:
Medical Imaging 1995: Image Processing
Murray H. Loew, Editor(s)

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