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Proceedings Paper

Efficient image reconstruction in fluorescence diffuse optical tomography (fDOT) using data and solution compression
Author(s): Teresa Correia; Timothy Rudge; Simon Arridge
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Paper Abstract

Current uorescence di use optical tomography (fDOT) systems can provide large data sets and, in addition, the unknown parameters to be estimated are so numerous that the sensitivity matrix is too large to store. Alternatively, iterative methods can be used, but they can be extremely slow at converging when dealing with large matrices. A few approaches suitable for the reconstruction of images from very large data sets have been developed. However, they either require explicit construction of the sensitivity matrix, su er from slow computation times or can only be applied to restricted geometries. We introduce a method for fast reconstruction in fDOT with large data and solution spaces, which preserves the resolution of the forward operator whilst compressing its representation. The method does not require construction of the full matrix, and thus, allows storage and direct inversion of the explicitly constructed compressed system matrix. The method is tested using simulated data. Results show that the fDOT image reconstruction problem can be e ectively compressed, without sigini cant loss of information and with the added advantage of reducing image noise.

Paper Details

Date Published: 14 June 2013
PDF: 9 pages
Proc. SPIE 8799, Diffuse Optical Imaging IV, 87990H (14 June 2013); doi: 10.1117/12.2032548
Show Author Affiliations
Teresa Correia, Univ. College London (United Kingdom)
Timothy Rudge, Univ. of Cambridge (United Kingdom)
Simon Arridge, Univ. College London (United Kingdom)


Published in SPIE Proceedings Vol. 8799:
Diffuse Optical Imaging IV
Paola Taroni; Hamid Dehghani, Editor(s)

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