Comprehensive investigation of three-dimensional diffuse optical tomography with depth compensation algorithm

Niu, Haijing; Lin, Zi Jing; Tian, Fenghua; Dhamne, Sameer C.; Liu, Hanli

doi:10.1117/1.3462986

Cited by 46 publications

(62 citation statements)

References 30 publications

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“…Quantitative comparative studies, using both simulated and in vivo data, have demonstrated clear improvements in resolution of the tomography approach (Boas et al, 2004a;Boas et al, 2004b;Boas et al, 2001;Koch et al, 2010;White and Culver, 2010b). While elegant depth compensation algorithms have been proposed to increase the quality of depth localization of DOT (Niu et al, 2010), a full comparison of such methods is beyond the scope of the present work. The spatially-dependent regularization techniques use herein for human DOT have been detailed in references: White and Culver, 2010a, b;White et al, 2009;Zeff et al, 2007).…”

Section: Discussionmentioning

confidence: 98%

A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping

Eggebrecht

White

Ferradal

et al. 2012

Biomedical Optics and 3-D Imaging

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Functional neuroimaging commands a dominant role in current neuroscience research. However its use in bedside clinical and certain neuro-scientific studies has been limited because the current tools lack the combination of being non-invasive, non-ionizing and portable while maintaining moderate resolution and localization accuracy. Optical neuroimaging satisfies many of these requirements, but, until recent advances in high-density diffuse optical tomography (HD-DOT), has been hampered by limited resolution. While early results of HD-DOT have been promising, a quantitative voxel-wise comparison and validation of HD-DOT against the gold standard of functional magnetic resonance imaging (fMRI) has been lacking. Herein, we provide such an analysis within the visual cortex using matched visual stimulation protocols in a single group of subjects (n=5) during separate HD-DOT and fMRI scanning sessions. To attain the needed voxelto-voxel co-registration between HD-DOT and fMRI image spaces, we implemented subjectspecific head modeling that incorporated MRI anatomy, detailed segmentation, and alignment of source and detector positions. Comparisons of the visual responses found an average localization error between HD-DOT and fMRI of 4.4 +/− 1 mm, significantly less than the average distance between cortical gyri. This specificity demonstrates that HD-DOT has sufficient image quality to be useful as a surrogate for fMRI.

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Section: Discussionmentioning

confidence: 98%

A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping

Eggebrecht

White

Ferradal

et al. 2012

Biomedical Optics and 3-D Imaging

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“…The detailed derivation and validation of DCA can be found in references [18,19]. The key component in DCA is the formation of a transformation matrix A # , as defined by A # = AM.…”

Section: Depth Compensation Algorithmmentioning

confidence: 99%

“…SVR has been utilized in the frequency-domain and CW-based DOT techniques for imaging human breast cancer and brain functions. Recently, we have developed a depth compensation algorithm (DCA) to significantly improve the accuracy of DOT in depth localization, as demonstrated by both laboratory phantom and human brain measurements [18,19], using fiber-based DOT systems.…”

Section: Introductionmentioning

confidence: 99%

Volumetric Diffuse Optical Tomography for Small Animals Using a CCD-Camera-Based Imaging System

Lin

Niu

Lin

et al. 2012

International Journal of Optics

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We report the feasibility of three-dimensional (3D) volumetric diffuse optical tomography for small animal imaging by using a CCD-camera-based imaging system with a newly developed depth compensation algorithm (DCA). Our computer simulations and laboratory phantom studies have demonstrated that the combination of a CCD camera and DCA can significantly improve the accuracy in depth localization and lead to reconstruction of 3D volumetric images. This approach may present great interests for noninvasive 3D localization of an anomaly hidden in tissue, such as a tumor or a stroke lesion, for preclinical small animal models.

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“…One such important task in DOT is the detection of absorptive heterogeneous regions, which we refer to as the signal, within the tissue. In DOT, often the anomalous regions are distinguished by a higher absorption coefficient compared to the rest of the tissue [17][18][19][20][21][22]. However, the sensitivity of diffuse-light measurements drops off quickly with penetration depth due to the high scattering in the tissue, which leads to poor depth resolution in DOT [23,24].…”

Section: Introductionmentioning

confidence: 99%

“…Metrics such as contrast-to-noise ratio (CNR) and positional errors (PE) [17,18,24,28] have been used to evaluate the performance of depth resolution provided by DOT reconstruction algorithms. The PE metric quantifies the error in locating a signal, while the CNR gives a measure of the whether the object can be detected from the background.…”

Section: Introductionmentioning

confidence: 99%

An ideal-observer framework to investigate signal detectability in diffuse optical imaging

Jha¹,

Clarkson²,

Kupinski³

2013

Biomed. Opt. Express

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With the emergence of diffuse optical tomography (DOT) as a non-invasive imaging modality, there is a requirement to evaluate the performance of the developed DOT systems on clinically relevant tasks. One such important task is the detection of high-absorption signals in the tissue. To investigate signal detectability in DOT systems for system optimization, an appropriate approach is to use the Bayesian ideal observer, but this observer is computationally very intensive. It has been shown that the Fisher information can be used as a surrogate figure of merit (SFoM) that approximates the ideal observer performance. In this paper, we present a theoretical framework to use the Fisher information for investigating signal detectability in DOT systems. The usage of Fisher information requires evaluating the gradient of the photon distribution function with respect to the absorption coefficients. We derive the expressions to compute the gradient of the photon distribution function with respect to the scattering and absorption coefficients. We find that computing these gradients simply requires executing the radiative transport equation with a different source term. We then demonstrate the application of the SFoM to investigate signal detectability in DOT by performing various simulation studies, which help to validate the proposed framework and also present some insights on signal detectability in DOT. In vivo hemoglobin and water concentrations, oxygen saturation, and scattering estimates from near-infrared breast tomography using spectral reconstruction," Acad. Radiol. 13, 195-202 (2006).

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Comprehensive investigation of three-dimensional diffuse optical tomography with depth compensation algorithm

Cited by 46 publications

References 30 publications

A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping

A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping

Volumetric Diffuse Optical Tomography for Small Animals Using a CCD-Camera-Based Imaging System

An ideal-observer framework to investigate signal detectability in diffuse optical imaging

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