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http://dx.doi.org/10.17946/JRST.2016.39.2.12

Singular Value Decomposition based Noise Reduction Technique for Dynamic PET I mage : Preliminary study  

Pyeon, Do-Yeong (Department of Health Science, Dongseo University)
Kim, Jung-Su (Department of Radiological Science, Dongnam Health University)
Baek, Cheol-Ha (Department of Health Science, Dongseo University)
Jung, Young-Jin (Department of Health Science, Dongseo University)
Publication Information
Journal of radiological science and technology / v.39, no.2, 2016 , pp. 227-236 More about this Journal
Abstract
Dynamic positron emission tomography(dPET) is widely used medical imaging modality that can provide both physiological and functional neuro-image for diagnosing various brain disease. However, dPET images have low spatial-resolution and high noise level during spatio-temporal analysis (three-dimensional spatial information + one-dimensional time information), there by limiting clinical utilization. In order to overcome these issues for the spatio-temporal analysis, a novel computational technique was introduced in this paper. The computational technique based on singular value decomposition classifies multiple independent components. Signal components can be distinguished from the classified independent components. The results show that signal to noise ratio was improved up to 30% compared with the original images. We believe that the proposed computational technique in dPET can be useful tool for various clinical / research applications.
Keywords
Dynamic Positron Emission Tomography (dPET); Singular Value Decomposition (SVD); Noise reduction;
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