Compressive sensing based reconstruction in bioluminescence tomography improves image resolution and robustness to noise

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Compressive sensing based reconstruction in bioluminescence tomography improves image resolution and robustness to noise. / Basevi, Hector R A; Tichauer, Kenneth M; Leblond, Frederic; Dehghani, Hamid; Guggenheim, James A; Holt, Robert W; Styles, Iain B.

In: Biomedical Optics Express, Vol. 3, No. 9, 01.09.2012, p. 2131-41.

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@article{40784c768b014bbf8f4088c06170615b,
title = "Compressive sensing based reconstruction in bioluminescence tomography improves image resolution and robustness to noise",
abstract = "Bioluminescence Tomography attempts to quantify 3-dimensional luminophore distributions from surface measurements of the light distribution. The reconstruction problem is typically severely under-determined due to the number and location of measurements, but in certain cases the molecules or cells of interest form localised clusters, resulting in a distribution of luminophores that is spatially sparse. A Conjugate Gradient-based reconstruction algorithm using Compressive Sensing was designed to take advantage of this sparsity, using a multistage sparsity reduction approach to remove the need to choose sparsity weighting a priori. Numerical simulations were used to examine the effect of noise on reconstruction accuracy. Tomographic bioluminescence measurements of a Caliper XPM-2 Phantom Mouse were acquired and reconstructions from simulation and this experimental data show that Compressive Sensing-based reconstruction is superior to standard reconstruction techniques, particularly in the presence of noise.",
author = "Basevi, {Hector R A} and Tichauer, {Kenneth M} and Frederic Leblond and Hamid Dehghani and Guggenheim, {James A} and Holt, {Robert W} and Styles, {Iain B}",
year = "2012",
month = sep
day = "1",
doi = "10.1364/BOE.3.002131",
language = "English",
volume = "3",
pages = "2131--41",
journal = "Biomedical Optics Express",
issn = "2156-7085",
publisher = "Optical Society of America",
number = "9",

}

RIS

TY - JOUR

T1 - Compressive sensing based reconstruction in bioluminescence tomography improves image resolution and robustness to noise

AU - Basevi, Hector R A

AU - Tichauer, Kenneth M

AU - Leblond, Frederic

AU - Dehghani, Hamid

AU - Guggenheim, James A

AU - Holt, Robert W

AU - Styles, Iain B

PY - 2012/9/1

Y1 - 2012/9/1

N2 - Bioluminescence Tomography attempts to quantify 3-dimensional luminophore distributions from surface measurements of the light distribution. The reconstruction problem is typically severely under-determined due to the number and location of measurements, but in certain cases the molecules or cells of interest form localised clusters, resulting in a distribution of luminophores that is spatially sparse. A Conjugate Gradient-based reconstruction algorithm using Compressive Sensing was designed to take advantage of this sparsity, using a multistage sparsity reduction approach to remove the need to choose sparsity weighting a priori. Numerical simulations were used to examine the effect of noise on reconstruction accuracy. Tomographic bioluminescence measurements of a Caliper XPM-2 Phantom Mouse were acquired and reconstructions from simulation and this experimental data show that Compressive Sensing-based reconstruction is superior to standard reconstruction techniques, particularly in the presence of noise.

AB - Bioluminescence Tomography attempts to quantify 3-dimensional luminophore distributions from surface measurements of the light distribution. The reconstruction problem is typically severely under-determined due to the number and location of measurements, but in certain cases the molecules or cells of interest form localised clusters, resulting in a distribution of luminophores that is spatially sparse. A Conjugate Gradient-based reconstruction algorithm using Compressive Sensing was designed to take advantage of this sparsity, using a multistage sparsity reduction approach to remove the need to choose sparsity weighting a priori. Numerical simulations were used to examine the effect of noise on reconstruction accuracy. Tomographic bioluminescence measurements of a Caliper XPM-2 Phantom Mouse were acquired and reconstructions from simulation and this experimental data show that Compressive Sensing-based reconstruction is superior to standard reconstruction techniques, particularly in the presence of noise.

U2 - 10.1364/BOE.3.002131

DO - 10.1364/BOE.3.002131

M3 - Article

C2 - 23024907

VL - 3

SP - 2131

EP - 2141

JO - Biomedical Optics Express

JF - Biomedical Optics Express

SN - 2156-7085

IS - 9

ER -