A PDE-constrained optimization approach to optical tomography

Xuejun Gu, Andreas H. Hielscher

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We report on the first formulation of the inverse problem in optical tomography within the framework of PDE-constrained optimization and combine Newton's method for numerical optimization with a Krylov subspace solver. This approach leads to reduced memory requirements and increased convergence speed.

Original languageEnglish (US)
Title of host publicationBiomedical Optics, BIOMED 2008
StatePublished - 2008
EventBiomedical Optics, BIOMED 2008 - St. Petersburg, FL, United States
Duration: Mar 16 2008Mar 19 2008

Other

OtherBiomedical Optics, BIOMED 2008
CountryUnited States
CitySt. Petersburg, FL
Period3/16/083/19/08

Fingerprint

pulse detonation engines
Optical tomography
Constrained optimization
Newton-Raphson method
Inverse problems
tomography
Data storage equipment
Newton methods
optimization
formulations
requirements

ASJC Scopus subject areas

  • Biomedical Engineering
  • Biomaterials
  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics

Cite this

Gu, X., & Hielscher, A. H. (2008). A PDE-constrained optimization approach to optical tomography. In Biomedical Optics, BIOMED 2008

A PDE-constrained optimization approach to optical tomography. / Gu, Xuejun; Hielscher, Andreas H.

Biomedical Optics, BIOMED 2008. 2008.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Gu, X & Hielscher, AH 2008, A PDE-constrained optimization approach to optical tomography. in Biomedical Optics, BIOMED 2008. Biomedical Optics, BIOMED 2008, St. Petersburg, FL, United States, 3/16/08.
Gu X, Hielscher AH. A PDE-constrained optimization approach to optical tomography. In Biomedical Optics, BIOMED 2008. 2008
Gu, Xuejun ; Hielscher, Andreas H. / A PDE-constrained optimization approach to optical tomography. Biomedical Optics, BIOMED 2008. 2008.
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