Flexible near-infrared diffuse optical tomography with varied weighting functions of edge-preserving regularization

Liang Yu Chen, Min Cheng Pan, Min Chun Pan

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

In this paper, a flexible edge-preserving regularization algorithm based on the finite element method is proposed to reconstruct the optical-property images of near-infrared diffuse optical tomography. This regularization algorithm can easily incorporate with varied weighting functions, such as a generalized Lorentzian function, an exponential function, or a generalized total variation function. To evaluate the performance, results obtained from Tikhonov or edge-preserving regularization are compared with each other. As found, the edge-preserving regularization with the generalized Lorentzian function is more attractive than that with other functions for the estimation of absorption-coefficient images concerning functional tomographic images to discover functional information of tested phantoms/tissues.

Original languageEnglish
Pages (from-to)1173-1182
Number of pages10
JournalApplied Optics
Volume52
Issue number6
DOIs
StatePublished - 20 Feb 2013

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