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The cascading of logic gates is one of the primary challenges for spintronic computing, as there is a need to dynamically create magnetic fields. Spin-diode logic provides this essential cascading, as the current through each spin-diode is modulated by a magnetic field created by the current through other spin-diodes. This logic family can potentially be applied to any device exhibiting strong positive or negative magnetoresistance, and allows for the creation of circuits with exceptionally high performance. These novel circuit structures provide an opportunity for spintronics to replace CMOS in general-purpose computing.

A continuous wave (CW) 94-GHz millimeter wave (mmW) standoff biosensor has been developed for remote biometric sensing applications. The sensor measures the demodulated in-phase (I) and quadrature-phase (Q) components of the received reflected mmW signal from a subject. Both amplitude and phase of the reflected signal are obtained from downconverted I and Q channels from the quadrature mixer. The mmW sensor can faithfully monitor human vital signs (heartbeat and respiration) at relatively long standoff distances. Principle Component Analysis (PCA) is used to extract the heartbeat, the respiration and the body motion signals. The approach allows one to deduce information about amplitude and beat-to-beat rate of the respiration and the heartbeat. Experimental results collected from a subject were analyzed and compared to the signal obtained with a three-electrode ECG monitoring instrument.

A modified polarized Monte Carlo code is developed that allows heterogeneous structure to be modeled. The code is validated with existent polarized Monte Carlo code. Heterogeneous structure simulating colon tissue is simulated to understand the difference between simulations of homogeneous vs heterogeneous tissue structure. Reflectance measurements from simulations containing increased blood vessel size and increased blood volume fraction, both markers for potential cancerous tissue, are studied in order to better interpret reflectance measurement from diagnostic probes.

In this paper, we develop an algorithm for obtaining the maximum a posteriori (MAP) estimate of the displacement vector field (DVF) from two consecutive image frames of an image sequence acquired under quantum-limited conditions. The estimation of the DVF has applications in temporal filtering, object tracking, and frame registration in low-light level image sequences as well as low-dose clinical x-ray image sequences. The quantum-limited effect is modeled as an undesirable, Poisson-distributed, signal-dependent noise artifact. The specification of priors for the DVF allows a smoothness constraint for the vector field. In addition, discontinuities of the field are taken into account through the introduction of a line process for neighboring vectors. A Bayesian formulation is used in this paper to estimate the DVF and a block component algorithm is employed in obtaining a solution. Several experiments involving a phantom sequence show the effectiveness of this estimator in obtaining the DVF under severe quantum noise conditions.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Clinical x-ray image sequences acquired through fluoroscopy systems may be corrupted by quantum mottle--a Poisson-distributed, signal-dependent noise that arises with a controlled x- ray dosage reduction in an attempt to lower the exposure to the patient and the medical staff. In this paper, an approach to temporally filter this sequence is presented. It relies on a joint estimation of the signal and the displacement field through a maximum likelihood approach. Implementation is done via a modified EM algorithm to facilitate a more tractable solution.© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

This paper deals with the estimation of the motion field in digital angiographic sequences. An approach is developed according to which each frame is first segmented into a moving object of interest and the background. The original images are converted into binary images by using a Gaussian smoothing filter and thresholding. In the binary images pixels in moving objects have the value of " 1" and pixels in the background have the value of " 0" . The moving objects in the binary images are thinned to skeletons with unit width by using the Safe-Point Thinning Algorithm (SPTA) with restriction windows we introduce. Then a block-matching algorithm is used in estimating the motion for the pixels which belong to the skeleton. This approach to motion estimation results in reduced computations since only binary multiplications need to be performed for determining the match between two blocks. Therefore an effective searching method is proposed for finding the direction of displacement in successive skeleton frames. Very satisfactory results are obtained by applying the algorithm to 64 x 64. pixel digital angiographic image sequences. 1© (1991) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A method is described for the computer simulation of quantum mottle in digital angiographic images obtained through an image intensifier (II) based system. The model corrupts a "perfect" image-one taken at high exposure levels-with Poisson distributed noise to simulate an image obtained through a lower x-ray dose. A mapping scheme is employed which effectively correlates gray level intensities at the image display to photon fluence at the front end of the II. The utility of the noise model is demonstrated by using it to simulate the effect of variable x-ray exposure conditions on an angiographic sequence. Such a sequence is valuable in the development of temporal filtering techniques for digital angiography.