Diffusion optical tomography using entropic priors

  • Authors:

  • Christos Panagiotou;Sangeetha Somayajula;Adam P. Gibson;Martin Schweiger;Richard M. Leahy;Simon R. Arridge

  • Affiliations:

  • Dept. of Medical Physics & Bioengineering, University College London;Signal and Image Processing Institute, University of Southern California;Dept. of Medical Physics & Bioengineering, University College London;Dept. of Computing Science, University College London;Signal and Image Processing Institute, University of Southern California;Dept. of Computing Science, University College London

  • Venue:
  • ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
  • Year:
  • 2009

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Abstract

Diffuse optical tomography (DOT) is a functional imaging modality which aims to retrieve the optical characteristics of the probed tissue, namely light absorption and diffusion. The accurate retrieval of the spatial distribution for each optical characteristic involves the solution of a highly-ill posed, non-linear inverse problem, thus employing a regularization is essential. In this work, we propose an entropic regularization scheme for DOT reconstruction that uses a priori structural information through mutual information (MI) and joint entropy (JE). We compare MI and JE through simulations that illustrate their behavior when the reference and DOT images are not identical in structure. We propose an efficient implementation of these regularizers based on fast Fourier transforms. The method is tested through numerical simulations.