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Vector extrapolation methods for accelerating iterative reconstruction methods in limited-data photoacoustic tomography

Awasthi, Navchetan and Kalva, Sandeep Kumar and Pramanik, Manojit and Yalavarthy, Phaneendra K (2018) Vector extrapolation methods for accelerating iterative reconstruction methods in limited-data photoacoustic tomography. In: JOURNAL OF BIOMEDICAL OPTICS, 23 (7).

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Official URL: http://dx.doi.org/10.1117/1.JBO.23.7.071204

Abstract

As limited data photoacoustic tomographic image reconstruction problem is known to be ill-posed, the iterative reconstruction methods were proven to be effective in terms of providing good quality initial pressure distribution. Often, these iterative methods require a large number of iterations to converge to a solution, in turn making the image reconstruction procedure computationally inefficient. In this work, two variants of vector polynomial extrapolation techniques were deployed to accelerate two standard iterative photoacoustic image reconstruction algorithms, including regularized steepest descent and total variation regularization methods. It is shown using numerical and experimental phantom cases that these extrapolation methods that are proposed in this work can provide significant acceleration (as high as 4.7 times) along with added advantage of improving reconstructed image quality. (c) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)

Item Type: Journal Article
Additional Information: Copy right for this article belong to SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS, 1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98225 USA
Department/Centre: Division of Interdisciplinary Research > Supercomputer Education & Research Centre
Depositing User: Id for Latest eprints
Date Deposited: 30 Aug 2018 15:41
Last Modified: 30 Aug 2018 15:41
URI: http://eprints.iisc.ac.in/id/eprint/60535

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