Fast and memory-efficient Monte Carlo-based image reconstruction for whole-body PET

Autor: Iwan Kawrakow, Jeroen Verhaeghe, Long Zhang, Steven Staelens, Stefaan Vandenberghe, Roel Van Holen, Jan De Beenhouwer
Rok vydání: 2010
Předmět:
Zdroj: Medical Physics. 37:3667-3676
ISSN: 0094-2405
Popis: Purpose: Several studies have shown the benefit of an accurate system modeling using Monte Carlo techniques. For state-of-the-art whole-body positron emission tomography(PET)scanners, Monte Carlo-based image reconstruction is associated with a significant computational cost to calculate the system matrix as well as a large memory capacity to store it. In this article, the authors present a simulation-reconstruction framework to solve these problems on the Philips Gemini GS PETscanner. Methods: A fast, realistic system matrix simulation module was developed using egs_pet, which is an efficient PET simulation code based on EGSnrc. The generated system matrix was then used in a rotator-based ordered subset expectation maximization (OS-EM) algorithm, which exploits the rotational symmetry of a cylindrical PETscanner. The system matrix was further compressed by using sparse storage techniques. Results: The system matrix simulation took five days on 50 cores of Xeon 2.66 GHz, resulting in a system matrix of 2.01 GB. The entire system matrix could be stored in the main memory of a standard personal computer. The image quality in terms of contrast-noise trade-offs was considerably improved compared to a standard OS-EM algorithm. The image quality was also compared to the clinical software on the scanner using routine parameter settings. The contrast recovery coefficient of small hot spheres and cold spheres was significantly improved. Conclusions: The results indicated that the proposed framework could be used for this PETscanner with improved image quality. This method could also be applied to other state-of-the-art whole-body PETscanners and preclinical PETscanners with a similar shape.
Databáze: OpenAIRE
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