Simultaneous imaging and optode calibration with diffuse optical tomography

Boas, David A.; Gaudette, Thomas J.; Arridge, Simon R.

doi:10.1364/oe.8.000263

Cited by 107 publications

(93 citation statements)

References 21 publications

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“…Recent advances, such as inclusion of coupling errors as a part of reconstruction scheme by making them as unknowns and iteratively solving for them along with optical parameters, are possible. [34][35][36][37] But this makes the reconstruction problem more computationally complex in nature as the number of unknowns of this procedure are larger than the techniques considered here. As the main focus of this article is about presenting a computationally efficient algorithm for reconstructing optical parameters, this issue was not considered as a part of this work.…”

Section: Discussionmentioning

confidence: 99%

Implementation of a computationally efficient least‐squares algorithm for highly under‐determined three‐dimensional diffuse optical tomography problems

et al. 2008

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Three-dimensional ͑3D͒ diffuse optical tomography is known to be a nonlinear, ill-posed and sometimes under-determined problem, where regularization is added to the minimization to allow convergence to a unique solution. In this work, a generalized least-squares ͑GLS͒ minimization method was implemented, which employs weight matrices for both data-model misfit and optical properties to include their variances and covariances, using a computationally efficient scheme. This allows inversion of a matrix that is of a dimension dictated by the number of measurements, instead of by the number of imaging parameters. This increases the computation speed up to four times per iteration in most of the under-determined 3D imaging problems. An analytic derivation, using the Sherman-Morrison-Woodbury identity, is shown for this efficient alternative form and it is proven to be equivalent, not only analytically, but also numerically. Equivalent alternative forms for other minimization methods, like Levenberg-Marquardt ͑LM͒ and Tikhonov, are also derived. Three-dimensional reconstruction results indicate that the poor recovery of quantitatively accurate values in 3D optical images can also be a characteristic of the reconstruction algorithm, along with the target size. Interestingly, usage of GLS reconstruction methods reduces error in the periphery of the image, as expected, and improves by 20% the ability to quantify local interior regions in terms of the recovered optical contrast, as compared to LM methods. Characterization of detector photomultiplier tubes noise has enabled the use of the GLS method for reconstructing experimental data and showed a promise for better quantification of target in 3D optical imaging. Use of these new alternative forms becomes effective when the ratio of the number of imaging property parameters exceeds the number of measurements by a factor greater than 2.

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Section: Discussionmentioning

confidence: 99%

Implementation of a computationally efficient least‐squares algorithm for highly under‐determined three‐dimensional diffuse optical tomography problems

et al. 2008

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“…42; with extensive calibration, ref. 43). The other major difficulty arises because the distance from the maternal abdomen to the fetal brain is 2-4 cm (19) in humans.…”

Section: Discussionmentioning

confidence: 99%

Transabdominal near infrared oximetry of hypoxic stress in fetal sheep brain in utero

Choe

Durdurán

et al. 2003

Proc. Natl. Acad. Sci. U.S.A.

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The feasibility of transabdominal near-infrared (NIR) spectroscopy for detecting and quantifying fetal hypoxia in utero is demonstrated in a pregnant ewe model. A frequency domain NIR spectroscopy probe, consisting of two detectors and six sources operating at three wavelengths (675, 786, and 830 nm), was placed on the maternal abdomen directly above the fetal head. Fetal hypoxia was indirectly induced through occlusion of uterine blood flow for Ϸ3 min. NIR photon diffusion measurements were made during a baseline period, during hypoxia of the fetus, and during recovery. Fetal blood samples were drawn from the fetal brachial artery and jugular veins at several time points during the cycle. Seven hypoxic cycles were induced in a total of five pregnant ewes. The NIR measurements were analyzed by using a two-layer diffusion model to deconvolve the fetal blood saturation from that of the pregnant ewe. Fetal hypoxia was detected. Good agreement was found between fetal blood saturation determined by the transabdominal NIR method and arterial and venous fetal blood saturation quantified from fetal blood samples by using a hemoximeter.

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“…For clinical data, we have found that, under compression, there are sufficient differences between our measurements and our model, even after calibration with a homogeneous phantom, that additional calibration parameters, one for each source and detector, must be introduced into the reconstruction (Boas et al 2001, Oh et al 2002. Thus, we make use of the following cost function: where s m and d n are source and detector amplitude calibration coefficients, respectively.…”

Section: Forward Model Cost Functions and Sensitivitiesmentioning

confidence: 99%

Spatio-temporal imaging of the hemoglobin in the compressed breast with diffuse optical tomography

Boverman¹,

Fang²,

Carp³

et al. 2007

Phys. Med. Biol.

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We develop algorithms for imaging the time-varying optical absorption within the breast given diffuse optical tomographic data collected over a time span that is long compared to the dynamics of the medium. Multispectral measurements allow for the determination of the time-varying total hemoglobin concentration and of oxygen saturation. To facilitate the image reconstruction, we decompose the hemodynamics in time into a linear combination of spatiotemporal basis functions, the coefficients of which are estimated using all of the data simultaneously, making use of a Newton-based nonlinear optimization algorithm. The solution of the extremely large least-squares problem which arises in computing the Newton update is obtained iteratively using the LSQR algorithm. A Laplacian spatial regularization operator is applied, and, in addition, we make use of temporal regularization which tends to encourage similarity between the images of the spatio-temporal coefficients. Results are shown for an extensive simulation, in which we are able to image and quantify localized changes in both total hemoglobin concentration and oxygen saturation. Finally, a breast compression study has been performed for a normal breast cancer screening subject, using an instrument which allows for highly accurate co-registration of multispectral diffuse optical measurements with an x-ray tomosynthesis image of the breast. We are able to quantify the global return of blood to the breast following compression, and, in addition,

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Simultaneous imaging and optode calibration with diffuse optical tomography

Cited by 107 publications

References 21 publications

Implementation of a computationally efficient least‐squares algorithm for highly under‐determined three‐dimensional diffuse optical tomography problems

Implementation of a computationally efficient least‐squares algorithm for highly under‐determined three‐dimensional diffuse optical tomography problems

Transabdominal near infrared oximetry of hypoxic stress in fetal sheep brain in utero

Spatio-temporal imaging of the hemoglobin in the compressed breast with diffuse optical tomography

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