A Method for Modeling Noise in PET Images
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2014, Vol 16, Issue 6
Abstract
Abstract: This paper will deal mainly with the performance study and analysis statistical properties of the noise found in various PET images. The method is specifically designed for types of noise produced by acquisition and transmission sequence in PET images. Here signal fluctuations generally originate in the physical processes of imaging rather than in the tissue textures. Various types of noise (transmission and quantization) often contribute to degrade PET images; the overall noise is generally assumed to be additive with a zero-mean, constant-variance Gaussian distribution. However, statistical analysis suggests that the noise variance could be better modeled by a nonlinear function of the image intensity depending on external parameters related to the image acquisition protocol. We present a method to extract the relationship between image intensity and the noise variance and to evaluate the corresponding parameters. The method was applied successfully to PET images with different acquisition sequences and transmission sequence.
Authors and Affiliations
Manolekshmi. I
Keywords
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