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A dimension reduction method for fast diffuse optical tomography
Author(s): Mingyu Choi; Jaemyoung Kim; Minsu Ji; Haeil Lee; Sungkwon Yu; Hyeon-min Bae
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Paper Abstract

Because the inverse problem in diffuse optical tomography (DOT) is highly ill-posed in general, appropriate regularization based on prior knowledge of the target is necessary for the reconstruction of the image. The total variation L1 norm regularization method (TV-L1) that preserves the boundaries of a target is known to have excellent result in image reconstruction. However, large computational cost of the TV-L1 prevents its use in portable applications. In this study, we propose a dimension reduction method in DOT for fast and hardware-efficient image reconstruction. The proposed method is based on the fact that the optical flux from a light source in a highly scattering medium is localized spatially. As such, the dimension of a sensitivity matrix used in the forward model of the DOT can be reduced by eliminating uncorrelated subspaces. The simulation results indicate up to 96.1% reduction in dimensions and up to 79.3% reduction in runtime while suppressing the reconstruction error below 2.26%.

Paper Details

Date Published: 24 May 2018
PDF: 8 pages
Proc. SPIE 10677, Unconventional Optical Imaging, 106770Y (24 May 2018); doi: 10.1117/12.2305691
Show Author Affiliations
Mingyu Choi, KAIST (Korea, Republic of)
Jaemyoung Kim, KAIST (Korea, Republic of)
Minsu Ji, KAIST (Korea, Republic of)
Haeil Lee, KAIST (Korea, Republic of)
Sungkwon Yu, KAIST (Korea, Republic of)
Hyeon-min Bae, KAIST (Korea, Republic of)


Published in SPIE Proceedings Vol. 10677:
Unconventional Optical Imaging
Corinne Fournier; Marc P. Georges; Gabriel Popescu, Editor(s)

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