PET image reconstruction using simulated annealing

Erik Sundermann; Ignace L. Lemahieu

doi:10.1117/12.208709

12 May 1995 PET image reconstruction using simulated annealing

Erik Sundermann, Ignace L. Lemahieu

Proceedings Volume 2434, Medical Imaging 1995: Image Processing; (1995) https://doi.org/10.1117/12.208709
Event: Medical Imaging 1995, 1995, San Diego, CA, United States

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.

Citation Download Citation

Erik Sundermann and Ignace L. Lemahieu "PET image reconstruction using simulated annealing", Proc. SPIE 2434, Medical Imaging 1995: Image Processing, (12 May 1995); https://doi.org/10.1117/12.208709

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available