We present analytical and numerical solutions to the problem of power control in wireless media systems with multiple antennas. We formulate a set of optimization problems aimed at minimizing total power consumption of wireless media systems subject to a given level of QoS and an available bit rate. Our formulation takes into consideration the power consumption related to source coding, channel coding, and transmission of multiple-transmit antennas. In our study, we consider Gauss-Markov and video source models, Rayleigh fading channels along with the Bernoulli/Gilbert-Elliott loss models, and space-time block codes.

In this research article, we present an analytical solution to the problem of power control in wireless media systems with multiple transmit antennas. We formulate an optimization problem aimed at minimizing total power consumption of wireless media systems subject to a given level of quality of service (QoS) and an available bit rate. Our formulation takes into consideration the power consumption related to source coding, channel coding, and transmission of multiple transmit antennas relying on the H.263 source coding standard, Rayleigh fading channels along with the Bernoulli loss model, and space-time block codes respectively.

Registering volumes that have been deformed with respect to each other involves recovery of the deformation. A 3-D elastic matching algorithm has been developed to use surface information for registering volumes. Surface extraction is performed in two steps: extraction of contours in 2-D image planes using active contours, and forming triangular patch surface models from the stack of 2-D contours. One volume is modeled as being deformed with respect to another goal volume. Correspondences between surfaces in the two image volumes are used to warp the deformed volume towards its goal. This process of contour extraction, surface formation and matching, and warping is repeated a number of times, with decreasing image volume stiffness. As the iterations continue the stretched volume is refined towards its goal volume. Registration examples of deformed volumes are presented.

Interpolation is a necessary step in magnetic resonance (MR) angiography when the center-to-center spacing between the MR slices is larger than the in-plane pixel size of the slices. Conventional methods interpolate normal to the slice only, causing a staircase artifact for oblique vessels. Reconstructions of these vessels demonstrate jagged structures with reduced resolution and contrast. A directional interpolation scheme is presented here, in which the orientation of interpolation is determined locally by template matching. By aligning this orientation with the vessels, the algorithm reconstructs the correct shape and contrast for oblique vessels. Simulations and application of the algorithm to clinical MR angiography data demonstrate the advantages of directional interpolation over conventional methods. Examples are shown of combining the algorithm with background suppression, where the background values in the slices are suppressed prior to projection and directional interpolation. This results in even higher vessel-to-background contrast.