Literature DB >> 19566336

Selection of regularization parameter for optical topography.

Teresa Correia1, Adam Gibson, Martin Schweiger, Jeremy Hebden.   

Abstract

The choice of the regularization parameter has a profound effect on the solution of ill-posed inverse problems such as optical topography. We review 11 different methods for selecting the Tikhonov regularization parameter that have been described previously in the literature. We test them on two trial problems, deblurring and optical topography, and conclude that the L-curve method is the method of choice, though in particularly ill-posed problems, generalized cross-validation may provide an alternative.

Mesh:

Year:  2009        PMID: 19566336     DOI: 10.1117/1.3156839

Source DB:  PubMed          Journal:  J Biomed Opt        ISSN: 1083-3668            Impact factor:   3.170


  3 in total

1.  Automatic selection of regularization parameters for dynamic fluorescence molecular tomography: a comparison of L-curve and U-curve methods.

Authors:  Maomao Chen; Han Su; Yuan Zhou; Chuangjian Cai; Dong Zhang; Jianwen Luo
Journal:  Biomed Opt Express       Date:  2016-11-09       Impact factor: 3.732

2.  Split operator method for fluorescence diffuse optical tomography using anisotropic diffusion regularisation with prior anatomical information.

Authors:  Teresa Correia; Juan Aguirre; Alejandro Sisniega; Judit Chamorro-Servent; Juan Abascal; Juan J Vaquero; Manuel Desco; Ville Kolehmainen; Simon Arridge
Journal:  Biomed Opt Express       Date:  2011-08-19       Impact factor: 3.732

3.  Dimensionality Reduction Based Optimization Algorithm for Sparse 3-D Image Reconstruction in Diffuse Optical Tomography.

Authors:  Tanmoy Bhowmik; Hanli Liu; Zhou Ye; Soontorn Oraintara
Journal:  Sci Rep       Date:  2016-03-04       Impact factor: 4.379

  3 in total

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