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Biomedical subjects

R Freyer

Publications and source records attributed to R Freyer.

At least 19 recordsLinked to original sources
PubMed2002

[Determination of tissue optical parameters using HF modulation spectroscopy].

Radio frequency modulation spectroscopy is a capable method to determine tissue optical parameters in-vivo. For the eventual purpose of clinical measurements we have developed and tested an rf laser spectroscopy device which enables a measurement of the spatial amplitude and phase shift profiles of backscattered modulated laser light. Spectral absorption and scattering coefficients are computed by inverse formulas derived from analytical solutions of the diffusion model of light transport in a semi-infinite geometry.

Humans↗
PubMed2002

[Modeling light distribution in nasal tissue structures].

There are different applications in the field of optical diagnostics in which the theories explaining the light transport in tissue do not lead to simple solutions for complicate geometric conditions. In these cases the Monte Carlo method provides a powerful tool to solve this problem statistically. In order to simulate the light transport in the nasal region a model was created which includes the structure depending on the swelling of the mucous membrane as well as the Monte Carlo model. Using this model it is possible to evaluate the measured values qualitatively. However, due to the long distance between light source and detector the statistical error becomes a major problem for reliable statements.

Humans↗
PubMed1998

Fast image reconstruction for optical absorption tomography in media with radially symmetric boundaries.

In this paper we present a reconstruction algorithm to invert the linearized problem in optical absorption tomography for objects with radially symmetric boundaries. This is a relevant geometry for functional volume imaging of body regions that are sensitive to ionizing radiation, e.g., breast and testis. From the principles of diffuse light propagation in scattering media we derive the governing integral equations describing the effects of absorption variations on changes in the measurement data. Expansion of these equations into a Neumann series and truncation of higher-order terms yields the linearized forward imaging operator. For the proposed geometry we utilize an invariance property of this operator, which greatly reduces the problem dimensionality. This allows us to compute the inverse by singular value decomposition and consequently to apply regularization techniques based on the knowledge of the singular value spectrum. The inversion algorithm is highly efficient computing slice images as fast as convolution-backprojection algorithms in computed tomography (CT). To demonstrate the capacity of the inversion scheme we present reconstruction results for synthetic and phantom measurement data.

Algorithms↗