Least squares QR-based decomposition provides an efficient way of computing optimal regularization parameter in photoacoustic tomography

Shaw, Calvin B and Prakash, Jaya and Pramanik, Manojit and Yalavarthy, Phaneendra K (2013) Least squares QR-based decomposition provides an efficient way of computing optimal regularization parameter in photoacoustic tomography. In: JOURNAL OF BIOMEDICAL OPTICS, 18 (8).

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Abstract

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. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)

Item Type:	Journal Article
Publication:	JOURNAL OF BIOMEDICAL OPTICS
Publisher:	SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
Additional Information:	Copyright of this article is belongs to SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
Keywords:	photoacoustic tomography; image reconstruction; regularization
Department/Centre:	Division of Electrical Sciences > Electrical Engineering Division of Interdisciplinary Sciences > Supercomputer Education & Research Centre
Date Deposited:	18 Oct 2013 05:10
Last Modified:	18 Oct 2013 05:10
URI:	http://eprints.iisc.ac.in/id/eprint/47526

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