Choosing the ART relaxation parameter for Clear-PEM 2D image reconstruction

Abstract The Algebraic Reconstruction Technique (ART) is an iterative image reconstruction algorithm. During the development of the Clear-PEM device, a PET scanner designed for the evaluation of breast cancer, multiple tests were done in order to optimise the reconstruction process. The comparison b...

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Bibliographic Details
Published in:Computer methods and programs in biomedicine 2010-05, Vol.98 (2), p.183-190
Main Authors: Mesquita, J, Matela, N, Oliveira, N, Martins, M.V, Almeida, P
Format: Article
Language:English
Subjects:
Algorithms
Biological and medical sciences
Breast Neoplasms - diagnostic imaging
Emission tomography
Female
Humans
Image Processing, Computer-Assisted - statistics & numerical data
Image reconstruction
Internal Medicine
Iterative algorithms
Likelihood Functions
Medical sciences
MLEM
Models, Statistical
OSEM
Other
Phantoms, Imaging
Positron emission mammography
Positron-Emission Tomography - statistics & numerical data
Radiotherapy. Instrumental treatment. Physiotherapy. Reeducation. Rehabilitation, orthophony, crenotherapy. Diet therapy and various other treatments (general aspects)
Relaxation parameter
Technology. Biomaterials. Equipments. Material. Instrumentation
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Summary:Abstract The Algebraic Reconstruction Technique (ART) is an iterative image reconstruction algorithm. During the development of the Clear-PEM device, a PET scanner designed for the evaluation of breast cancer, multiple tests were done in order to optimise the reconstruction process. The comparison between ART, MLEM and OSEM indicates that ART can perform faster and with better image quality than the other, most common algorithms. It is claimed in this paper that if ART's relaxation parameter is carefully adjusted to the reconstruction procedure it can produce high quality images in short computational time. This is confirmed by showing that with the relaxation parameter evolving as a logarithmic function, ART can match in terms of image quality and overcome in terms of computational time the performance of MLEM and OSEM algorithms. However, this study was performed only with simulated data and the level of noise with real data may be different.
ISSN:0169-2607
1872-7565
DOI:10.1016/j.cmpb.2009.11.010