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RTE-based parameter reconstruction with [formula omitted] regularization.
- Source :
-
Journal of Computational & Applied Mathematics . Aug2018, Vol. 337, p256-273. 18p. - Publication Year :
- 2018
-
Abstract
- Optical tomography is an imaging modality that explores the distribution of optical parameters in tissues. In this paper, the regularization jointing both T V and L 1 norm is studied for absorption parameter identification based on radiative transport equation. The T V + L 1 framework is introduced containing L 2 data fidelity, T V regularizer and L 1 regularizer. We demonstrate the existence, stability and convergence of the minima with respect to this T V + L 1 regularization. A novel algorithm for solving related optimization problem is proposed based on reweighted method and technique of split-Bregman. Simulations are performed to show that the proposed reweighted T V + L 1 regularization is more capable of preserving geometric structure of inclusions, quantifying values of absorption parameter and promoting fast convergence compared with T V or L 1 regularization, and is potential for breast cancer imaging. Moreover, it is robust to noise. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03770427
- Volume :
- 337
- Database :
- Academic Search Index
- Journal :
- Journal of Computational & Applied Mathematics
- Publication Type :
- Academic Journal
- Accession number :
- 128348459
- Full Text :
- https://doi.org/10.1016/j.cam.2018.01.011