20 October 2016 Computationally efficient error estimate for evaluation of regularization in photoacoustic tomography
Author Affiliations +
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, Atithi Acharya, 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:
JOURNAL ARTICLE
9 PAGES


SHARE
Back to Top