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Biomedical subjects

Andreas H Hielscher

Publications and source records attributed to Andreas H Hielscher.

5 recordsLinked to original sources

Optical tomographic imaging of small animals.

Diffuse optical tomography is emerging as a viable new biomedical imaging modality. Using visible and near-infrared light this technique can probe the absorption and scattering properties of biological tissues. The main applications are currently in brain, breast, limb and joint imaging; however, optical tomographic imaging of small animals is attracting increasing attention. This interest is fuelled by recent advances in the transgenic manipulation of small animals that has led to many models of human disease. In addition, an ever increasing number of optically reactive biochemical markers has become available, which allow diseases to be detected at the molecular level long before macroscopic symptoms appear. The past three years have seen an array of novel technological developments that have led to the first optical tomographic studies of small animals in the areas of cerebral ischemia and cancer.

Animals↗

Sagittal laser optical tomography for imaging of rheumatoid finger joints.

We present a novel optical tomographic imaging system that was designed to determine two-dimensional spatial distribution of optical properties in a sagittal plane through finger joints. The system incorporates a single laser diode and a single silicon photodetector into a scanning device that records spatially resolved light intensities as they are transmitted through a finger. These data are input to a model-based iterative image reconstruction (MOBIIR) scheme, which uses the equation of radiative transfer (ERT) as a forward model for light propagation through tissue. We have used this system to obtain tomographic images of six proximal interphalangeal finger joints from two patients with rheumatoid arthritis. The optical images were compared to clinical symptoms and ultrasound images.

Algorithms↗

Algorithm for solving the equation of radiative transfer in the frequency domain.

We present an algorithm that provides a frequency-domain solution of the equation of radiative transfer (ERT) for heterogeneous media of arbitrary shape. Although an ERT is more accurate than a diffusion equation, no ERT code for the widely employed frequency-domain case has been developed to date. In this work the ERT is discretized by a combination of discrete-ordinate and finite-volume methods. Two numerical simulations are presented.

Algorithms↗

Parallel programming of gradient-based iterative image reconstruction schemes for optical tomography.

Optical tomography (OT) is a fast developing novel imaging modality that uses near-infrared (NIR) light to obtain cross-sectional views of optical properties inside the human body. A major challenge remains the time-consuming, computational-intensive image reconstruction problem that converts NIR transmission measurements into cross-sectional images. To increase the speed of iterative image reconstruction schemes that are commonly applied for OT, we have developed and implemented several parallel algorithms on a cluster of workstations. Static process distribution as well as dynamic load balancing schemes suitable for heterogeneous clusters and varying machine performances are introduced and tested. The resulting algorithms are shown to accelerate the reconstruction process to various degrees, substantially reducing the computation times for clinically relevant problems.

Algorithms↗

Fluorescence tomography with simulated data based on the equation of radiative transfer.

The quantification of a nonuniform quantum yield or fluorophore absorption distribution is of major interest in molecular imaging of biological tissue. We introduce what is believed to be the first fluorescence image reconstruction algorithm based on the equation of radiative transfer that recovers the spatial distribution of light-emitting fluorophores inside a highly scattering medium from measurements made on the surface of the medium. We obtain images of either the quantum yield or the fluorophore absorption.

Algorithms↗