Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/37821
Title: A study on static image derived input function for non-invasively constructing parametric image in functional imaging
Authors: Shi, X
Wen, L
Cai, W
Feng, D
Keywords: Functional imaging
Kinetic modelling
Non-invasive method
Positron emission tomography
Issue Date: 2011
Source: Proceedings of the International Conference on Digital Image Computing Techniques and Applications (DICTA'2011), Noosa, Queensland, Australia, 6-8 Dec. 2011, p. 314-318 How to cite?
Abstract: Positron emission tomography (PET), as functional imaging, provides in-vivo spatial distribution of physiological or biochemical processes. The kinetic modelling process to derive quantitative functional parameter usually requires invasive frequent blood sampling. We proposed a new approach to use static imaging derived information to produce non-invasive input function (SID-IF). The performance of SID-IF was investigated by 609 clinical neurological studies in non-invasively constructing parametric images of cerebral metabolic rate of glucose consumption (CMRGlc). The performance of the personal information feature based input function method (PIFB-IF) was also evaluated in the investigation. The results of area under curve and CMRGlc demonstrated the image feature derived by cerebellum provided less bias in the estimation of SID-IF. The performance of SID-IF was sensitive to the choice of the training set and the plasma glucose concentration in the data set may improve the estimated accuracy. The PIFB-IF method was less sensitive to the glucose range and choice of training set.
URI: http://hdl.handle.net/10397/37821
ISBN: 978-1-4577-2006-2
DOI: 10.1109/DICTA.2011.59
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