title: Optical imaging of phantoms from real data by an approximately globally convergent inverse algorithm.
abstract: A numerical method for an inverse problem for an elliptic equation with the running source at multiple positions is presented. This algorithm does not rely on a good first guess for the solution. The so-called "approximate global convergence" property of this method is shown here. The performance of the algorithm is verified on real data for Diffusion Optical Tomography. Direct applications are in near-infrared laser imaging technology for stroke detection in brains of small animals.
authors.affiliation: Department of Mathematics, University of Texas at Arlington, Arlington, TX 76019, USA.
authors.forename: Jianzhong
authors.initials: J
authors.lastname: Su
authors.forename: Michael V
authors.initials: MV
authors.lastname: Klibanov
authors.forename: Yueming
authors.initials: Y
authors.lastname: Liu
authors.forename: Zhijin
authors.initials: Z
authors.lastname: Lin
authors.forename: Natee
authors.initials: N
authors.lastname: Pantong
authors.forename: Hanli
authors.initials: H
authors.lastname: Liu
keywords: Approximate Global Convergence Property; Diffusion Optical Tomography; Inverse Problem; Real Data