Reconstruction algorithm for near-infrared imaging in turbid media by means of time-domain data

Diffuse optical tomography (DOT) retrieves the spatially distributed optical characteristics of a medium from external measurements. Recovering these parameters of interest involves solving a non-linear and severely ill-posed inverse problem. In this thesis we propose methods towards the regularization of DOT via the introduction of spatially unregistered, a priori information from alternative high resolution anatomical modalities, using the information theory concepts of joint entropy (JE) and mutual information (MI). Such functionals evaluate the similarity between the reconstructed optical image and the prior image, while bypassing the multi-modality barrier manifested as the incommensurate relation between the gray value representations of corresponding anatomical features in the modalities involved. By introducing structural a priori information in the image reconstruction process, we aim to improve the spatial resolution and quantitative accuracy of the solution.A further condition for the accurate incorporation of a priori information is the establishment of correct alignment between the prior image and the probed anatomy in a common coordinate system. However, limited information regarding the probed anatomy is known prior to the reconstruction process.In this work we explore the potentiality of spatially registering the prior image simultaneously with the solution of the reconstruction process.We provide a thorough explanation of the theory from an imaging perspective, accompanied by preliminary results obtained by numerical simulations as well as experimental data. In addition we compare the performance of MI and JE. Finally, we propose a method for fast joint entropy evaluation and optimization, which we later employ for the information theoretic regularization of DOT. The main areas involved in this thesis are: inverse problems, image reconstruction & regularization, diffuse optical tomography and medical image registration. Statement of intellectual contributionI, Christos Panagiotou, declare that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been properly indicated in the thesis.

show abstract

“…2.4.3. It has been used in multiple studies in DOT including [Boverman et al, 2005;Model et al, 1997;Pogue et al, 1995].…”

Section: Quadratic Penalties (Gaussian Priors)mentioning

confidence: 99%

Information theoretic regularization in diffuse optical tomography

Panagiotou¹,

Somayajula²,

Gibson³

et al. 2009

J. Opt. Soc. Am. A

View full text Add to dashboard Cite

show abstract

“…In these cases, sources and receivers are commonly located along perimeters of the object cross sections at equal step angles. [2][3][4][5][6][7] If the source and the receiver are sufficiently removed from each other, the PAT approximation by a broken line is acceptable. Our investigations show that by choosing the optimal values of the time-gating delay of receivers, the length of the middle segment of the broken PAT may be longer than the first and end ones.…”

Section: Reconstruction Problem Statementmentioning

confidence: 99%

“…1 To solve the inverse problem of ODT, iterative Newton-and gradient-like methods based on the numerical simulation of optical inhomogeneities inside a phantom with the characteristics of a researched object are commonly used. [2][3][4][5][6][7][8][9][10] The problem of light migration is repeatedly solved as long as simulated signals on the phantom surface are comparable with those really measured. Generally, the spatial resolution of the images restored using such methods is not better than 1 cm, which is adequate only for restricted medical applications of ODT.…”

Section: Introductionmentioning

confidence: 99%

Application of transform algorithms to high-resolution image reconstruction in optical diffusion tomography of strongly scattering media

Konovalov

Lyubimov

Kutuzov

et al. 2003

J. Electron. Imaging

View full text Add to dashboard Cite

The applicability of transform algorithms generally used in projection-computed tomography is substantiated for the case of medical optical diffusion tomography (ODT). To reconstruct tissue optical inhomogeneities, a new method based on a concept of an average statistical trajectory for transfer of light energy [photon average trajectory (PAT)] is proposed. By this method, the inverse problem of ODT is reduced to a solution of an integral equation with integration along a PAT. Within the internal zone of the object, well away from the boundaries, PATs tend to a straight line, and standard integral algorithms based on the inverse Radon transform may be used to restore diffuse optical images. To demonstrate the capabilities of the PAT method, a numerical experiment on cross sectional reconstruction of cylindrical strongly scattering objects with lowcontrast absorbing inhomogeneities is conducted. To solve the timedomain ODT inverse problem, two filtered backprojection algorithms (of Radon and Vainberg) are used. The reconstruction results are compared with those obtained by a well-known software package for temporal optical absorption and scattering tomography, based on multiple solutions of a diffusion equation. It is shown that in important cases of low-contrast absorbing inhomogeneities, the PAT method using the Vainberg algorithm allows reconstruction of tissue optical inhomogeneities with a 20% gain in spatial resolution.

show abstract

“…In these cases sources and receivers are commonly located along perimeters of the object cross-sections at equal step angles [2][3][4][5][6][7] . If the source and the receiver are sufficiently removed from each other, the PAT approximation by a broken line is acceptable.…”

Section: Reconstruction Problem Statementmentioning

confidence: 99%

“…The direct application of standard reconstruction methods based on an assumption of the existence of rectilinear photon trajectories leads to considerable image faults 1 . To solve the inverse problem of DOT, iterative Newton-like and gradient-like methods based on numerical simulation of optical inhomogeneities inside the phantom with characteristics of a researched object are commonly used [2][3][4][5][6][7][8][9][10] . The problem of light migration is repeatedly solved as long as simulated signals on the phantom surface are comparable with those really measured.…”

Section: Introductionmentioning

confidence: 99%

Application of integral transform algorithms to high-resolution reconstruction of tissue inhomogeneities in medical diffuse optical tomography

Konovalov¹,

Lyubimov

Kutuzov³

et al. 2002

Optics in Health Care and Biomedical Optics: Diagnostics and Treatment

View full text Add to dashboard Cite

The applicability of the transform algorithms generally used in projection computed tomography is substantiated for the case of medical diffuse optical tomography (DOT). To reconstruct tissue optical inhomogeneities, a new method based on a concept of an average statistical trajectory for transfer of light energy (photon average trajectory, PAT) is proposed. By this method, the inverse problem of DOT is reduced to solution of integral equation with integration along a PAT. Within the internal zone of the object, remote well away from the boundaries, PATs tend to a straight line, and standard integral algorithms based on the inverse Radon transform may be used to restore diffuse optical images. To demonstrate the capabilities of the PAT method, a numerical experiment on cross-sectional reconstruction of cylindrical strongly scattering objects with absorbing inhomogeneities has been conducted. To solve the DOT inverse problem, two filtered backprojection algorithms (of Radon and of Vainberg) were used. The reconstruction results are compared with those obtained by a well-known software package for temporal optical absorption and scattering tomography, based on multiple solution of diffusion equation. It is shown that the PAT method using the Vainberg algorithm allows reconstruction of tissue optical structure with a 20%-gain in spatial resolution.

show abstract

Reconstruction algorithm for near-infrared imaging in turbid media by means of time-domain data

Cited by 25 publications

References 17 publications

Information theoretic regularization in diffuse optical tomography

Information theoretic regularization in diffuse optical tomography

Application of transform algorithms to high-resolution image reconstruction in optical diffusion tomography of strongly scattering media

Application of integral transform algorithms to high-resolution reconstruction of tissue inhomogeneities in medical diffuse optical tomography

Contact Info

Product

Resources

About