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Proceedings Paper

Compensated Tikhonov regularization for quantitative perfusion measurements
Author(s): Behzad Ebrahimi; Timothy E. Chupp
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Paper Abstract

Truncated singular value decomposition and Tikhonov regularization are the most popular methods in perfusion model deconvolution. The first method uses a global truncation threshold and the second method uses a global regularization matrix. In this research a pixel-specific Tikhonov-based regularization, as well as a novel optimization based approach for bolus delay correction are suggested. The two techniques can be integrated into an iterative process. The new approach implements prior information to improve the regularization of the residue function and reduce the underestimation of flow rate. To compare its accuracy with current methods, deconvolution and delay correction for different perfusion related parameters and noise levels were simulated. Based on the simulation results, the new method showed more accuracy in preserving the structural shape of the residue function and estimating the perfusion-related parameters, especially in low SNRs.

Paper Details

Date Published: 12 March 2008
PDF: 11 pages
Proc. SPIE 6916, Medical Imaging 2008: Physiology, Function, and Structure from Medical Images, 69160O (12 March 2008); doi: 10.1117/12.769707
Show Author Affiliations
Behzad Ebrahimi, Univ. of Michigan (United States)
Timothy E. Chupp, Univ. of Michigan (United States)


Published in SPIE Proceedings Vol. 6916:
Medical Imaging 2008: Physiology, Function, and Structure from Medical Images
Xiaoping P. Hu; Anne V. Clough, Editor(s)

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