Pinhole imaging is a promising approach for high spatial resolution single gamma emission
imaging in situations when the required field of view (FOV) is small, as is the case for small
animal imaging. However, all pinhole collimators exhibit steep decrease in sensitivity with
increasing angle of incidence from the pinhole axis. This in turn degrades the reconstruction
images, and requires higher dose of radiotracer. We developed a novel pinhole SPECT system
for small animal imaging which uses two opposing and offset small cone-angle square
pinholes, each looking at half of the FOV. This design allows the pinholes to be placed closer to
the object and greatly increases detection efficiency and spatial resolution, while not requiring
larger size detectors. Iterative image reconstruction algorithms for this system have been developed. Preliminary experimental data have demonstrated marked improvement in contrast and spatial resolution.
Obtaining hight quality ultrasound images at high frame rates has great medical importance, especially in applications where tissue motion is significant (e.g. the beating heart). Dynamic focusing and dynamic apodization can improve image quality significantly, and they have been implemented on the receive beam in state-of-the-art medical ultrasound systems. However implementing dynamic focusing and dynamic apodization on the transmit beam compromises frame rate. We present a novel transmit apodization scheme where a continuum of focal points can be obtained in one transmission, and uniform sensitivity and uniform point spread function can be achieved over very large range without reducing frame rate. Preliminary simulations demonstrate significant promises of the new technique.
We propose an algebraic reconstruction technique (ART) in the frequency domain for linear imaging problems. This algorithm has the advantage of efficiently incorporating pixel correlations in an a priori image model. First it is shown that the generalized ART algorithm converges to the minimum weighted norm solution, where the weights represent a priori knowledge of the image. Then an implementation in the frequency domain is described. The performance of the new algorithm is demonstrated with a fan beam computed tomography (CT) example. Compared to the traditional ART, the new algorithm offers superior image quality, fast convergence, and moderate complexity.
We propose a family of new algorithms that can be viewed as a generalization of the Algebraic Reconstruction Techniques (ART). These algorithms can be tailored for trade-offs between convergence speed and memory requirement. They also can be made to include Gaussian a priori image models. A key advantage is that they can handle arbitrary data acquisition scheme. Approximations are required for practical sized image reconstruction. We discuss several approximations and demonstrate numerical simulation examples for computed tomography (CT) reconstructions.
A novel close form solution to resolve the directions of arrival (azimuth and elevation) of two sources using a single snapshot (monopulse) is presented, the technique is first formulated for a 2 X 2 array, and then extended to the more common amplitude comparison monopulse channels. Limitations, error analysis, and simulation results are also discussed.
We describe a jamming cancellation algorithm for wide-band imaging radar. After reviewing high range resolution imaging principle, several key factors affecting jamming cancellation performances, such as the 'instantaneous narrow-band' assumption, bandwidth, de-chirped interference, are formulated and analyzed. Some numerical simulation results, using a hypothetical phased array radar and synthetic point targets, are presented. The results demonstrated the effectiveness of the proposed algorithm.
A new monopulse 3D imaging algorithm based on the Prony's method is presented. The algorithm does not suffer from the down-range resolution limit and cross-range glint error of a traditional Fourier transform based imaging algorithm. Imaging errors due to thermal noise are analyzed for both algorithms. A simulation examples is described.
Three methods for reconstructing icosahedrally-symmetric particles from solution x-ray scattering data are described. Such data is the spherical average of the magnitude-squared of the Fourier transform of the electron density in the particle and therefore is only one dimensional. Because of the limited amount of data, a priori information about the particle is crucial and the three methods differ in the description of the particle that is used. This type of reconstruction problem is important in the structural biology of spherical viruses, and example reconstructions from one such virus are described.
A model-based method for reconstructing the 3D structure of icosahedrally-symmetric viruses from solution x-ray scattering is presented. An example of the reconstruction, for data from cowpea mosaic virus, is described. The major opportunity provided by solution x-ray scattering is the ability to study the dynamics of virus particles in solution, information that is not accessible to crystal x-ray diffraction experiments.