Least squares QR-based decomposition provides an efficient way of computing optimal regularization parameter in photoacoustic tomography
Shaw, Calvin B.
Yalavarthy, Phaneendra K.
Date of Issue2013
School of Chemical and Biomedical Engineering
A computationally efficient approach that computes the optimal regularization parameter for the Tikhonov-minimization scheme is developed for photoacoustic imaging. This approach is based on the least squares-QR decomposition which is a well-known dimensionality reduction technique for a large system of equations. It is shown that the proposed framework is effective in terms of quantitative and qualitative reconstructions of initial pressure distribution enabled via finding an optimal regularization parameter. The computational efficiency and performance of the proposed method are shown using a test case of numerical blood vessel phantom, where the initial pressure is exactly known for quantitative comparison.
Journal of biomedical optics
© 2013 Society of Photo-Optical Instrumentation Engineers (SPIE). This paper was published in Journal of Biomedical Optics and is made available as an electronic reprint (preprint) with permission of Society of Photo-Optical Instrumentation Engineers (SPIE). The paper can be found at the following official DOI: [http://dx.doi.org/10.1117/1.JBO.18.8.080501]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.