Spectrally constrained L1-norm improves quantitative accuracy of diffuse optical tomography

Wenqi Lu; Iain B. Styles

doi:10.1117/12.2285996

Spectrally constrained L₁-norm improves quantitative accuracy of diffuse optical tomography

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We consider L1-regularization of spectrally constrained DOT. Three popular algorithms are investigated: iteratively reweighted least square algorithm (IRLS), alternating directional method of multipliers (ADMM) and fast iterative shrinkage-thresholding algorithm (FISTA). We evaluate different regularizers and algorithms on a 3D simulated multi-spectral example.

Original language	English
Title of host publication	Proceedings of SPIE 10412 Diffuse Optical Spectroscopy and Imaging VI,-
Publisher	Society of Photo-Optical Instrumentation Engineers
DOIs	https://doi.org/10.1117/12.2285996
Publication status	Published - 28 Jul 2017
Externally published	Yes

Access to Document

10.1117/12.2285996Licence: Unspecified

Cite this

@inproceedings{d8e2e67589d3468daac9b0f215bc6af5,

title = "Spectrally constrained L1-norm improves quantitative accuracy of diffuse optical tomography",

abstract = "We consider L1-regularization of spectrally constrained DOT. Three popular algorithms are investigated: iteratively reweighted least square algorithm (IRLS), alternating directional method of multipliers (ADMM) and fast iterative shrinkage-thresholding algorithm (FISTA). We evaluate different regularizers and algorithms on a 3D simulated multi-spectral example.",

author = "Wenqi Lu and Styles, \{Iain B.\}",

year = "2017",

month = jul,

day = "28",

doi = "10.1117/12.2285996",

language = "English",

booktitle = "Proceedings of SPIE 10412 Diffuse Optical Spectroscopy and Imaging VI,-",

publisher = "Society of Photo-Optical Instrumentation Engineers",

}

TY - GEN

T1 - Spectrally constrained L1-norm improves quantitative accuracy of diffuse optical tomography

AU - Lu, Wenqi

AU - Styles, Iain B.

PY - 2017/7/28

Y1 - 2017/7/28

N2 - We consider L1-regularization of spectrally constrained DOT. Three popular algorithms are investigated: iteratively reweighted least square algorithm (IRLS), alternating directional method of multipliers (ADMM) and fast iterative shrinkage-thresholding algorithm (FISTA). We evaluate different regularizers and algorithms on a 3D simulated multi-spectral example.

AB - We consider L1-regularization of spectrally constrained DOT. Three popular algorithms are investigated: iteratively reweighted least square algorithm (IRLS), alternating directional method of multipliers (ADMM) and fast iterative shrinkage-thresholding algorithm (FISTA). We evaluate different regularizers and algorithms on a 3D simulated multi-spectral example.

U2 - 10.1117/12.2285996

DO - 10.1117/12.2285996

M3 - Conference contribution

BT - Proceedings of SPIE 10412 Diffuse Optical Spectroscopy and Imaging VI,-

PB - Society of Photo-Optical Instrumentation Engineers

ER -

Spectrally constrained L1-norm improves quantitative accuracy of diffuse optical tomography

Abstract

Access to Document

Fingerprint

Cite this

Spectrally constrained L₁-norm improves quantitative accuracy of diffuse optical tomography