logo
CanyamAI summaries for academic research
language
MobileMobile
  • Phone FeatureWeChat Mini Program
EnglishEnglish
noticeNotice
BlogBlog
delete
arrow
Return

Three-dimensional Bayesian optical diffusion tomography with experimental data

delete2002-01-15
delete50
PRE
AI
A
Adam B. Milstein *
S
Seungseok Oh
J
Jeffery S. Reynolds
K
Kevin J. Webb
C
Charles A. Bouman
R
Rick P. Millane
DOI：10.1364/OL.27.000095delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Reconstructions of a three-dimensional absorber embedded in a scattering medium by use of frequency domain measurements of the transmitted light in a single source-detector plane are presented. The reconstruction algorithm uses Bayesian regularization and iterative coordinate descent optimization, and it incorporates estimation of the detector noise level, the source-detector coupling coefficient, and the background diffusion coefficient in addition to the absorption image. The use of multiple modulation frequencies is also investigated. The results demonstrate the utility of this algorithm, the importance of a three-dimensional model, and that out-of-plane scattering permits recovery of three-dimensional features from measurements in a single plane. (C) 2002 Optical Society of America.

Journal

Optics Letters cover
Optics Letters
IF:
3.3
Papers:
4.0W
Citations:
7.6W

Organization

No organization information available