Algorithm for localized adaptive diffuse optical tomography and its application in bioluminescence tomography

Mohamed A. Naser, Michael S. Patterson, John Wong

Research output: Contribution to journalArticle

Abstract

A reconstruction algorithm for diffuse optical tomography based on diffusion theory and finite element method is described. The algorithm reconstructs the optical properties in a permissible domain or region-of-interest to reduce the number of unknowns. The algorithm can be used to reconstruct optical properties for a segmented object (where a CT-scan or MRI is available) or a non-segmented object. For the latter, an adaptive segmentation algorithm merges contiguous regions with similar optical properties thereby reducing the number of unknowns. In calculating the Jacobian matrix the algorithm uses an efficient direct method so the required time is comparable to that needed for a single forward calculation. The reconstructed optical properties using segmented, non-segmented, and adaptively segmented 3D mouse anatomy (MOBY) are used to perform bioluminescence tomography (BLT) for two simulated internal sources. The BLT results suggest that the accuracy of reconstruction of total source power obtained without the segmentation provided by an auxiliary imaging method such as x-ray CT is comparable to that obtained when using perfect segmentation.

Original languageEnglish (US)
Pages (from-to)2089-2109
Number of pages21
JournalPhysics in Medicine and Biology
Volume59
Issue number8
DOIs
StatePublished - Apr 21 2014

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Keywords

  • bioluminescence
  • diffuse optical tomography
  • medical and biological imaging
  • tomography

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology

Cite this

Algorithm for localized adaptive diffuse optical tomography and its application in bioluminescence tomography. / Naser, Mohamed A.; Patterson, Michael S.; Wong, John.

In: Physics in Medicine and Biology, Vol. 59, No. 8, 21.04.2014, p. 2089-2109.

Research output: Contribution to journalArticle

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