Reduction of Poisson noise in measured time-resolved data for time-domain diffuse optical tomography View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2012-01

AUTHORS

S. Okawa, Y. Endo, Y. Hoshi, Y. Yamada

ABSTRACT

A method to reduce noise for time-domain diffuse optical tomography (DOT) is proposed. Poisson noise which contaminates time-resolved photon counting data is reduced by use of maximum a posteriori estimation. The noise-free data are modeled as a Markov random process, and the measured time-resolved data are assumed as Poisson distributed random variables. The posterior probability of the occurrence of the noise-free data is formulated. By maximizing the probability, the noise-free data are estimated, and the Poisson noise is reduced as a result. The performances of the Poisson noise reduction are demonstrated in some experiments of the image reconstruction of time-domain DOT. In simulations, the proposed method reduces the relative error between the noise-free and noisy data to about one thirtieth, and the reconstructed DOT image was smoothed by the proposed noise reduction. The variance of the reconstructed absorption coefficients decreased by 22% in a phantom experiment. The quality of DOT, which can be applied to breast cancer screening etc., is improved by the proposed noise reduction. More... »

PAGES

69-78

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11517-011-0774-7

DOI

http://dx.doi.org/10.1007/s11517-011-0774-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1013824011

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/21499803


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