Research Papers: Imaging

Computationally efficient error estimate for evaluation of regularization in photoacoustic tomography

[+] Author Affiliations
Manish Bhatt, Atithi Acharya, Phaneendra K. Yalavarthy

Indian Institute of Science, Medical Imaging Group, Department of Computational and Data Sciences, C V Raman Avenue, Bengaluru 560012, India

J. Biomed. Opt. 21(10), 106002 (Oct 20, 2016). doi:10.1117/1.JBO.21.10.106002
History: Received June 17, 2016; Accepted September 14, 2016
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Abstract.  The model-based image reconstruction techniques for photoacoustic (PA) tomography require an explicit regularization. An error estimate (η2) minimization-based approach was proposed and developed for the determination of a regularization parameter for PA imaging. The regularization was used within Lanczos bidiagonalization framework, which provides the advantage of dimensionality reduction for a large system of equations. It was shown that the proposed method is computationally faster than the state-of-the-art techniques and provides similar performance in terms of quantitative accuracy in reconstructed images. It was also shown that the error estimate (η2) can also be utilized in determining a suitable regularization parameter for other popular techniques such as Tikhonov, exponential, and nonsmooth (1 and total variation norm based) regularization methods.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Manish Bhatt ; Atithi Acharya and Phaneendra K. Yalavarthy
"Computationally efficient error estimate for evaluation of regularization in photoacoustic tomography", J. Biomed. Opt. 21(10), 106002 (Oct 20, 2016). ; http://dx.doi.org/10.1117/1.JBO.21.10.106002


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