Biomedical subjects

Jason Riley

Publications and source records attributed to Jason Riley.

3 recordsLinked to original sources

PubMed2005

Local diffusion regularization method for optical tomography reconstruction by using robust statistics.

We formulate a solution to the diffuse optical tomography (DOT) inverse problem as the minimization of an energy functional of the solution and the data. For the solution prior we introduce a local diffusion regularization potential with a threshold based on robust statistics (the Hubert function). We compare results on simulated data for the Hubert function and two other standard regularization functionals, Tikhonov and total variation.

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PubMed2005

Linear and nonlinear reconstruction for optical tomography of phantoms with nonscattering regions.

Most research in optical imaging incorrectly assumes that light transport in nonscattering regions in the head may be modeled by use of the diffusion approximation. The effect of this assumption is examined in a series of experiments on tissue-equivalent phantoms. Images from cylindrical and head-shaped phantoms with and without clear regions [simulating the cerebrospinal fluid (CSF) filled ventricles] and a clear layer (simulating the CSF layer surrounding the brain) are reconstructed with linear and nonlinear reconstruction techniques. The results suggest that absorbing and scattering perturbations can be identified reliably with nonlinear reconstruction methods when the clear regions are also present in the reference data but that the quality of the image degrades considerably if the reference data does not contain these features. Linear reconstruction performs similarly to nonlinear reconstruction, provided the clear regions are present in the reference data, but otherwise linear reconstruction fails. This study supports the use of linear reconstruction for dynamic imaging but suggests that, in all cases, image quality is likely to improve if the clear regions are modeled correctly.

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PubMed2003

Optical tomography of a realistic neonatal head phantom.

We have begun clinical trials of optical tomography of the neonatal brain. To validate this research, we have built and imaged an anatomically realistic, tissue-equivalent neonatal head phantom that is hollow, allowing contrasting objects to be placed inside it. Images were reconstructed by use of two finite-element meshes, one generated from a computed tomography image of the phantom and the other spherical. The phantom was filled with a liquid of the same optical properties as the outer region, and two perturbations were placed inside. These were successfully imaged with good separation between the absorption and scatter coefficients. The phantom was then refilled with a liquid of increased absorption compared with the background to simulate the brain, and the absolute properties of the two regions were found. These were used as a priori information for the complete reconstruction. Both perturbations were visible, superimposed on the increased absorption of the central region. The head-shaped mesh performed slightly better than the spherical mesh, particularly when the absorption of the central region of the phantom was increased.

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