Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/37671
Title: Improved non-invasive quantification of physiological processes with dynamic PET using blind system identification
Authors: Lun, DPK 
Chan, TCL
Feng, DD
Keywords: Medical image processing
Parameter estimation
Physiology
Positron emission tomography
Issue Date: 2001
Source: Proceedings of 2001 International Symposium on Intelligent Multimedia, Video and Speech Processing, 2001, 02 May 2001-04 May 2001, Hong Kong, p. 255-258 How to cite?
Abstract: The traditional quantitative study using tracer kinetic modeling requires repeated blood sampling to measure the tracer concentration in plasma. It is invasive, time-consuming and costly. We propose a new approach to estimate physiological parameters for dynamic Positron Emission Tomography (PET) without taking blood samples. With the new approach, the quantification problem is first converted to a discrete blind system identification problem. A multi-channel blind identification technique is applied to estimate the required system parameters. A Monte Carlo simulation is carried out for the proposed approach on estimating the regional cerebral metabolic rate of glucose (rCMRGlc) with the fluoro-deoxy-2-glucose (FDG) model. The results show that the proposed approach can estimate the required physiological parameters in a comparable manner to that of traditional invasive approaches
URI: http://hdl.handle.net/10397/37671
ISBN: 962-85766-2-3
DOI: 10.1109/ISIMP.2001.925382
Appears in Collections:Conference Paper

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