1. Flexible near-infrared diffuse optical tomography with varied weighting functions of edge-preserving regularization
- Author
-
Min Cheng Pan, Min Chun Pan, and Liang Yu Chen
- Subjects
Diagnostic Imaging ,Optics and Photonics ,Finite Element Analysis ,Image processing ,Iterative reconstruction ,Regularization (mathematics) ,Diffusion ,Tikhonov regularization ,Optics ,Image Processing, Computer-Assisted ,Humans ,Tomography, Optical ,Computer Simulation ,Breast ,Poisson Distribution ,Electrical and Electronic Engineering ,Engineering (miscellaneous) ,Mathematics ,Phantoms, Imaging ,business.industry ,Models, Theoretical ,Inverse problem ,Atomic and Molecular Physics, and Optics ,Diffuse optical imaging ,Exponential function ,Weighting ,Female ,Electronics ,business ,Algorithm ,Algorithms - 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.
- Published
- 2013