z-logo
open-access-imgOpen Access
Improvement of image quality of time-domain diffuse optical tomography with lp sparsity regularization
Author(s) -
Shinpei Okawa,
Yoko Hoshi,
Yukio Yamada
Publication year - 2011
Publication title -
biomedical optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.2.003334
Subject(s) - regularization (linguistics) , diffuse optical imaging , imaging phantom , algorithm , attenuation coefficient , image resolution , tomography , physics , image quality , mathematics , mathematical analysis , optics , computer science , artificial intelligence , image (mathematics)
An l(p) (0 < p ≤ 1) sparsity regularization is applied to time-domain diffuse optical tomography with a gradient-based nonlinear optimization scheme to improve the spatial resolution and the robustness to noise. The expression of the l(p) sparsity regularization is reformulated as a differentiable function of a parameter to avoid the difficulty in calculating its gradient in the optimization process. The regularization parameter is selected by the L-curve method. Numerical experiments show that the l(p) sparsity regularization improves the spatial resolution and recovers the difference in the absorption coefficients between two targets, although a target with a small absorption coefficient may disappear due to the strong effect of the l(p) sparsity regularization when the value of p is too small. The l(p) sparsity regularization with small p values strongly localizes the target, and the reconstructed region of the target becomes smaller as the value of p decreases. A phantom experiment validates the numerical simulations.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here