20 October 2016 Computationally efficient error estimate for evaluation of regularization in photoacoustic tomography
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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.
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)
Manish Bhatt, Manish Bhatt, Atithi Acharya, Atithi Acharya, Phaneendra K. Yalavarthy, Phaneendra K. Yalavarthy, } "Computationally efficient error estimate for evaluation of regularization in photoacoustic tomography," Journal of Biomedical Optics 21(10), 106002 (20 October 2016). https://doi.org/10.1117/1.JBO.21.10.106002 . Submission:
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