The intima-media thickness (IMT) of the carotid artery is an important biomarker for the clinical prognosis and diagnosis of atherosclerosis and stroke. This paper presents a new approach, pixel compounding, to enhance the resolution of the intima-media vascular layers in ultrasound B-scan images and provide increased image resolution for a more precise measurement. First, homomorphic transformation is used to estimate the lumped point spread function (PSF) of the images, then, the images are deblurred with the estimated PSF, and finally, a non-homogeneous anisotropic diffusion algorithm is used to further enhance the resolution of the image. The homogeneous part of the algorithm is used to suppress speckle while enhancing the coherent structures, specifically the edges; the non-homogeneous part (likelihood estimator) progressively adds the details from succeeding frames in the image sequence for an optimal and sub-pixel resolved image. Phantom studies have shown 300% improvement on Peak Distance Standard Deviation and nearly 100% improvement on Average Half Peak Width, indicating significant resolution enhancement.
A new ultrasound technique for determining three-dimensional velocity vectors has been devised using radio frequency (RF) data from commercially available scanners. Applied to blood flow, this technique could prove useful for evaluating hemodynamics and detecting stenoses. Three orthogonal velocity vectors are computed from the RF signals of two steered beams from a single array. The in-plane velocities are determined using standard Doppler analysis, while the out-of-plane component is derived from the total velocity as computed from temporal decorrelation and the in-plane components. The technique was tested using contrast agent pumped through a flow tube. A GE Vingmed SystemV scanner with a 10 MHz linear array provided scans at beam steering angles of +/- 20 degree(s). Both Doppler velocities and temporal complex decorrelation were computed for each digitized voxel. Additional studies were done on a blood mimicking fluid and in vivo with a canine femoral artery. Vector plots were constructed to show flow for various transducer angles. Angle estimates were within 20 degree(s), and the mean error for the velocity amplitude was less than 15%. The in vivo results provided velocity estimates consistent with the literature. The proposed method, unlike current Doppler velocity measurement techniques, provides quantitative velocity information independent of transducer orientation.
Radial basis function neural network models of a time series may be developed or trained using samples from the series. Each model is a continuous curve that can be used to represent the series or predict future vales. Model development requires a tradeoff between a measure of roughness of the curve and a measure of its error relative to the samples. For roughness defined as the root integrated squared second derivative and for error defined as the root sum squared deviation (which are among the most common definitions), an optimal tradeoff conjecture is proposed and illustrated. The conjecture states that the curve that minimizes roughness subject to given error is a weighted mean of the least squares line and the natural cubic spline through the samples.
KEYWORDS: Convolution, Image processing, Visual process modeling, Visualization, Digital imaging, Digital image processing, Spatial resolution, Systems modeling, Image segmentation, Imaging systems
A digital image smoothing procedure is described that meets two requirements inferred from a recent model of biological vision. First, the smoothed image is a linear combination of basis functions formed by convolving a Gaussian function with each pixel. Second, the linear coefficients are evaluated by requiring that the integral of the smoothed image over each pixel equal the product of the gray value and area of that pixel. These requirement are in accordance with a model of visual hyperacuity that explains the ability of biological vision systems to resolve some image details that are much smaller than system photoreceptors. The procedure is demonstrated and compared with standard Gaussian convolution smoothing for both a simple one- dimensional example and a practical corner-of-an-eye test image.
A new technique for efficient speckle reduction in synthetic aperture radar (SAR) images using wavelet packets is proposed. A phenomenological approach is used in adapting the wavelet packet transform to minimize the speckle coefficients. With thresholding and averaging, the resulting non-linear, multirate filtering can be used to preprocess images for reduction of speckle while retaining contrast in key objects necessary for target classification. An example of the algorithm using a SAR image is provided.
Micromirror arrays are being developed that can have up to tens of thousands of micromirror elements, each as small as 20 microns on a side, each spaced relative to neighbors so that optical efficiency exceeds 90 percent, and each individually controlled with response times as small as 10 microseconds for piston-like phase-mostly displacements that cover more than one- half optical wavelength. These arrays may be well suited for active aberration control of the focused coherent beams used in many applications, including optical disk storage, optical scanning, and laser radar systems. Active aberration control requires determination of the voltage supplied to the micromirror array elements so that constructive and destructive interference in light reflected from many elements yields the desired result. This paper discussed an approach in which the voltages are determined off-line by simulated annealing optimization and stored for real-time use.
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