JBO Letters

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

[+] Author Affiliations
Calvin B. Shaw, Jaya Prakash, Phaneendra K. Yalavarthy

Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore 560012, India

Manojit Pramanik

Department of Electrical Engineering, Indian Institute of Science, Bangalore 560012, India

J. Biomed. Opt. 18(8), 080501 (Jul 31, 2013). doi:10.1117/1.JBO.18.8.080501
History: Received June 14, 2013; Revised July 4, 2013; Accepted July 9, 2013
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Abstract

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.

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© 2013 Society of Photo-Optical Instrumentation Engineers

Citation

Calvin B. Shaw ; Jaya Prakash ; Manojit Pramanik and Phaneendra K. Yalavarthy
"Least squares QR-based decomposition provides an efficient way of computing optimal regularization parameter in photoacoustic tomography", J. Biomed. Opt. 18(8), 080501 (Jul 31, 2013). ; http://dx.doi.org/10.1117/1.JBO.18.8.080501


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