Comparison of methods for optimal choice of the regularization parameter for linear electrical impedance tomography of brain function
Abascal, Juan-Felipe and Arridge, Simon R. and Bayford, Richard and Holder, David S. (2008) Comparison of methods for optimal choice of the regularization parameter for linear electrical impedance tomography of brain function. Physiological measurement, 29 (11). pp. 1319-1334. ISSN 0967-3334
Full text is not in this repository.
This item is available in the Library Catalogue
Electrical impedance tomography has the potential to provide a portable non-invasive method for imaging brain function. Clinical data collection has largely been undertaken with time difference data and linear image reconstruction methods. The purpose of this work was to determine the best method for selecting the regularization parameter of the inverse procedure, using the specific application of evoked brain activity in neonatal babies as an exemplar. The solution error norm and image SNR for the L-curve (LC), discrepancy principle (DP), generalized cross validation (GCV) and unbiased predictive risk estimator (UPRE) selection methods were evaluated in simulated data using an anatomically accurate finite element method (FEM) of the neonatal head and impedance changes due to blood flow in the visual cortex recorded in vivo. For simulated data, LC, GCV and UPRE were equally best. In human data in four neonatal infants, no significant differences were found among selection methods. We recommend that GCV or LC be employed for reconstruction of human neonatal images, as UPRE requires an empirical estimate of the noise variance.
|Research Areas:||School of Science and Technology > Natural Sciences|
|Citations on ISI Web of Science:||4|
|Deposited On:||21 May 2009 13:03|
|Last Modified:||04 Feb 2014 08:11|
Repository staff and depositor only: item control page
Full text downloads (NB count will be zero if no full text documents are attached to the record)
Downloads per month over the past year