Optimal linear inverse solution with multiple priors in diffuse optical tomography

A general framework for incorporating single and multiple priors in diffuse optical tomography is described. We explore the use of this framework for simultaneously utilizing spatial and spectral priors in the context of imaging breast cancer. The utilization of magnetic resonance images of water an...

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Bibliographic Details
Published in:Applied optics (2004) 2005-04, Vol.44 (10), p.1948-1956
Main Authors: Li, Ang, Boverman, Greg, Zhang, Yiheng, Brooks, Dana, Miller, Eric L, Kilmer, Misha E, Zhang, Quan, Hillman, Elizabeth M C, Boas, David A
Format: Article
Language:English
Subjects:
Algorithms
Brain Mapping - methods
Humans
Image Interpretation, Computer-Assisted - instrumentation
Image Interpretation, Computer-Assisted - methods
Linear Models
Magnetic Resonance Imaging - methods
Models, Biological
Phantoms, Imaging
Reproducibility of Results
Sensitivity and Specificity
Spectroscopy, Near-Infrared - instrumentation
Spectroscopy, Near-Infrared - methods
Tomography, Optical - instrumentation
Tomography, Optical - methods
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Description
Summary:A general framework for incorporating single and multiple priors in diffuse optical tomography is described. We explore the use of this framework for simultaneously utilizing spatial and spectral priors in the context of imaging breast cancer. The utilization of magnetic resonance images of water and lipid content as a statistical spatial prior for the diffuse optical image reconstructions is also discussed. Simulations are performed to demonstrate the significant improvement in image quality afforded by combining spatial and spectral priors.
ISSN:1559-128X
DOI:10.1364/AO.44.001948