학술논문

Diffusion optical tomography using entropic priors
Document Type
Conference
Source
2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on. :197-200 Jun, 2009
Subject
Bioengineering
Computing and Processing
Signal Processing and Analysis
Tomography
Nonlinear optics
US Department of Transportation
Optical imaging
Image retrieval
Absorption
Inverse problems
Image reconstruction
Mutual information
Entropy
Diffusion Optical Tomography
Regularization
Prior information
Joint entropy
Mutual Information
Language
ISSN
1945-7928
1945-8452
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.