title: Reduction of Poisson noise in measured time-resolved data for time-domain diffuse optical tomography.
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.
authors.affiliation: Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Tokyo, Japan. okawa@mce.uec.ac.jp
authors.forename: S
authors.initials: S
authors.lastname: Okawa
authors.forename: Y
authors.initials: Y
authors.lastname: Endo
authors.forename: Y
authors.initials: Y
authors.lastname: Hoshi
authors.forename: Y
authors.initials: Y
authors.lastname: Yamada
mesh_terms: D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008390:Markov Chains; D019047:Phantoms, Imaging; D016012:Poisson Distribution; D041622:Tomography, Optical / Q000379:methods*