Structural information within regularization matrices improves near infrared diffuse optical tomography

Research output: Contribution to journalArticle

Authors

  • Phaneendra K Yalavarthy
  • Brian W Pogue
  • Colin M Carpenter
  • Shudong Jiang
  • Keith D Paulsen

Colleges, School and Institutes

Abstract

Near-Infrared (NIR) tomographic image reconstruction is a non-linear, ill-posed and ill-conditioned problem, and so in this study, different ways of penalizing the objective function with structural information were investigated. A simple framework to incorporate structural priors is presented, using simple weight matrices that have either Laplacian or Helmholtz-type structures. Using both MRI-derived breast geometry and phantom data, a systematic and quantitative comparison was performed with and without spatial priors. The Helmholtz-type structure can be seen as a more generalized approach for incorporating spatial priors into the reconstruction scheme. Moreover, parameter reduction (i.e. hard prior information) in the imaging field through the enforcement of spatially explicit regions may lead to erroneous results with imperfect spatial priors.

Details

Original languageEnglish
Pages (from-to)8043-58
Number of pages16
JournalOptics Express
Volume15
Issue number13
Publication statusPublished - 25 Jun 2007