DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ye, Jong Chul | ko |
dc.contributor.author | Webb, KJ | ko |
dc.contributor.author | Bouman, CA | ko |
dc.contributor.author | Millane, RP | ko |
dc.date.accessioned | 2013-02-27T11:57:09Z | - |
dc.date.available | 2013-02-27T11:57:09Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 1999-10 | - |
dc.identifier.citation | JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, v.16, no.10, pp.2400 - 2412 | - |
dc.identifier.issn | 0740-3232 | - |
dc.identifier.uri | http://hdl.handle.net/10203/68420 | - |
dc.description.abstract | Frequency-domain diffusion imaging uses the magnitude and phase of modulated light propagating through a highly scattering medium to reconstruct an image of the spatially dependent scattering or absorption coefficients in the medium. An inversion algorithm is formulated in a Bayesian framework and an efficient optimization technique is presented for calculating the maximum a posteriori image. In this framework the data are modeled as a complex Gaussian random vector with shot-noise statistics, and the unknown image is modeled as a generalized Gaussian Markov random field. The shot-noise statistics provide correct weighting for the measurement, and the generalized Gaussian Markov random field prier enhances the reconstruction quality and retains edges in the reconstruction. A localized relaxation algorithm, the iterative-coordinate-descent algorithm, is employed as a computationally efficient optimization technique. Numerical results for two-dimensional images show that the Bayesian framework with the new optimization scheme outperforms conventional approaches in both speed and reconstruction quality. (C) 1999 Optical Society of America [S0740-3232(99)01410-6]. | - |
dc.language | English | - |
dc.publisher | OPTICAL SOC AMER | - |
dc.title | Optical diffusion tomography by iterative-coordinate-descent optimization in a Bayesian framework | - |
dc.type | Article | - |
dc.identifier.wosid | 000082836600009 | - |
dc.identifier.scopusid | 2-s2.0-0000828127 | - |
dc.type.rims | ART | - |
dc.citation.volume | 16 | - |
dc.citation.issue | 10 | - |
dc.citation.beginningpage | 2400 | - |
dc.citation.endingpage | 2412 | - |
dc.citation.publicationname | JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION | - |
dc.identifier.doi | 10.1364/JOSAA.16.002400 | - |
dc.contributor.localauthor | Ye, Jong Chul | - |
dc.contributor.nonIdAuthor | Webb, KJ | - |
dc.contributor.nonIdAuthor | Bouman, CA | - |
dc.contributor.nonIdAuthor | Millane, RP | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordPlus | PHOTON-DENSITY WAVES | - |
dc.subject.keywordPlus | IMAGE-RECONSTRUCTION | - |
dc.subject.keywordPlus | SCATTERING MEDIA | - |
dc.subject.keywordPlus | PROPAGATION | - |
dc.subject.keywordPlus | ABSORPTION | - |
dc.subject.keywordPlus | TISSUES | - |
dc.subject.keywordPlus | REFLECTANCE | - |
dc.subject.keywordPlus | ALGORITHM | - |
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