Abstract

A reconstruction algorithm for multiwavelength diffuse optical tomography is presented, where instead of using data at each wavelength separately or even simultaneously, the difference in data for multiple wavelength pairs is used to reconstruct absolute concentration maps of chromophores. The results indicate a dramatic improvement in image reconstruction and the elimination of image artifacts, which are often associated with unknown measurement errors such as coupling coefficients and external boundary variations, because these errors are often less dependent on wavelength, and are effectively removed from the data set of the first derivative of intensity with respect to wavelength.

© 2005 Optical Society of America

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References

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2005 (3)

2003 (2)

2001 (1)

1999 (1)

Arridge, S. R.

Barbour, R. L.

Boas, D. A.

Chance, B.

Choe, R.

Corlu, A.

Culver, J. P.

Dehghani, H.

Dunn, J. F.

Durduran, T.

Graber, H. L.

Heino, J.

Hillman, E. M.

Jiang, S.

Kaipio, J. P.

Ntziachristos, V.

Paulsen, K. D.

Pei, Y. L.

Pogue, B. W.

Schmitz, C. H.

Schweiger, M.

Somersalo, E.

Springett, R.

Srinivasan, S.

Stott, J. J.

Xu, H.

H. Xu, R. Springett, H. Dehghani, B. W. Pogue, K. D. Paulsen, and J. F. Dunn, Appl. Opt. 44, 2177 (2005).
[CrossRef] [PubMed]

H. Xu, “MRI-coupled broadband near-infrared tomography for small animal brain studies,” Ph.D. dissertation (Dartmouth College, 2005).

Yodh, A. G.

Zhong, S.

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Figures (4)

Fig. 1
Fig. 1

A, Experiment geometry and source–detector fiber configuration. B, Measured attenuation spectra at D1, D2 and their difference. C, First-order finite difference spectra of D1 and D2 with a 20 nm separation.

Fig. 2
Fig. 2

A, Target phantom with five distinct inclusions ( diameter = 27 mm ) . Each column corresponds to the particular parameter. B, Target phantom for a simulation where an irregular boundary was considered.

Fig. 3
Fig. 3

A–D, Reconstructed images of simulations for both SDIR (left) and DCSR (right), with A, images having no data errors; B, 5% randomly distributed coupling errors; C, boundary reflection coefficient modeling error; D, reconstructing data taken from a distorted boundary shape.

Fig. 4
Fig. 4

Reconstructed images of a liquid phantom for both A, SDIR and B, DCSR. The background was 0.03 mM fully oxygenated blood with 1% Intralipid and the inclusion contained in a thin and clear straw was 0.09 mM fully deoxygenated blood with 2% Intralipid.

Tables (1)

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Table 1 Properties of the Background Medium and Five Inclusions

Equations (3)

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Ψ 1 = Δ Φ c o 2 2 = { Φ λ 1 c ( x ) Φ λ 2 c ( x ) Φ λ m c ( x ) } { Φ λ 1 o Φ λ 2 o Φ λ m o } 2 2 .
I = [ I a I b I c 1 I c 2 I c 2 ] = [ I a , λ 1 I b , λ 1 I c 1 , λ 1 I c 2 , λ 1 I c 3 , λ 1 I a , λ 2 I b , λ 2 I c 1 , λ 2 I c 2 , λ 2 I c 3 , λ 2 I a , λ m I b , λ m I c 1 , λ m I c 2 , λ m I c 3 , λ m ] .
Ψ 2 = Δ Φ c o 2 2 = { Φ λ 1 c ( x ) Φ λ 2 c ( x ) Φ λ 2 c ( x ) Φ λ 3 c ( x ) Φ λ m 1 c ( x ) Φ λ m c ( x ) } { Φ λ 1 o Φ λ 2 o Φ λ 2 o Φ λ 3 o Φ λ m 1 o Φ λ m o } 2 2 .

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