Three-dimensional tomographic reconstruction of mesospheric airglow structures using two-station ground-based image measurements.

A new methodology is presented to create two-dimensional (2D) and three-dimensional (3D) tomographic reconstructions of mesospheric airglow layer structure using two-station all-sky image measurements. A fanning technique is presented that produces a series of cross-sectional 2D reconstructions, which are combined to create a 3D mapping of the airglow volume. The imaging configuration is discussed and the inherent challenges of using limited-angle data in tomographic reconstructions have been analyzed using artificially generated imaging objects. An iterative reconstruction method, the partially constrained algebraic reconstruction technique (PCART), was used in conjunction with a priori information of the airglow emission profile to constrain the height of the imaged region, thereby reducing the indeterminacy of the inverse problem. Synthetic projection data were acquired from the imaging objects and the forward problem to validate the tomographic method and to demonstrate the ability of this technique to accurately reconstruct information using only two ground-based sites. Reconstructions of the OH airglow layer were created using data recorded by all-sky CCD cameras located at Bear Lake Observatory, Utah, and at Star Valley, Wyoming, with an optimal site separation of ~100 km. The ability to extend powerful 2D and 3D tomographic methods to two-station ground-based measurements offers obvious practical advantages for new measurement programs. The importance and applications of mesospheric tomographic reconstructions in airglow studies, as well as the need for future measurements and continued development of techniques of this type, are discussed.

Simulation of elastic wave scattering in cells and tissues at the microscopic level.

The scattering of longitudinal and shear waves from spherical, nucleated cells and three-dimensional tissues with simple and hierarchical microstructures was numerically modeled at the microscopic level using an iterative multipole approach. The cells were modeled with a concentric core-shell (nucleus-cytoplasm) structure embedded in an extracellular matrix. Using vector multipole expansions and boundary conditions, scattering solutions were derived for single cells with either solid or fluid properties for each of the cell components. Tissues were modeled as structured packings of cells. Multiple scattering between cells was simulated using addition theorems to translate the multipole fields from cell to cell in an iterative process. Backscattering simulations of single cells indicated that changes in the shear properties and nuclear diameter had the greatest effect on the frequency spectra. Simulated wave field images and high-frequency spectra (15-75 MHz) from tissues containing 1211-2137 cells exhibited up to 20% enhancement of the field amplitudes at the plasma membrane, significant changes in spectral features due to neoplastic and other microstructural alterations, and a detection threshold of approximately 8.5% infiltration of tumor cells into normal tissue. These findings suggest that histology-based simulations may provide insight into fundamental ultrasound-tissue interactions and help in the development of new medical technologies.

Histology-based simulations for the ultrasonic detection of microscopic cancer in vivo.

Ultrasonic spectroscopy may offer an alternative to imaging methods for the in vivo detection of microscopic cancer. To investigate this potential, a numerical model that incorporates multiple scattering, wave-mode conversion, and hierarchical microstructures was developed to simulate ultrasonic interactions in biological tissue at the microscopic level. Simulated high-frequency (20-75 MHz) spectra of up to 2137 cells displayed significant correlations to nucleus diameter and malignant cell infiltration, and indicated as few as 300 malignant cells may be detectable in normal tissue. The results suggest that ultrasonic spectroscopy combined with simulation-based interpretive models may provide real-time histopathology during surgeries, biopsies, and endoscopies.