title: Local diffusion regularization method for optical tomography reconstruction by using robust statistics.
abstract: We formulate a solution to the diffuse optical tomography (DOT) inverse problem as the minimization of an energy functional of the solution and the data. For the solution prior we introduce a local diffusion regularization potential with a threshold based on robust statistics (the Hubert function). We compare results on simulated data for the Hubert function and two other standard regularization functionals, Tikhonov and total variation.
authors.affiliation: Department of Computer Science, University College London, Gower Street, London WC1E 6BT, UK.
authors.forename: Abdel
authors.initials: A
authors.lastname: Douiri
authors.forename: Martin
authors.initials: M
authors.lastname: Schweiger
authors.forename: Jason
authors.initials: J
authors.lastname: Riley
authors.forename: Simon
authors.initials: S
authors.lastname: Arridge
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D041622:Tomography, Optical / Q000379:methods*