A novel phantom and method for comprehensive 3-dimensional measurement and correction of geometric distortion in magnetic resonance imaging

A phantom that can be used for mapping geometric distortion in magnetic resonance imaging (MRI) is described. This phantom provides an array of densely distributed control points in three-dimensional (3D) space. These points form the basis of a comprehensive measurement method to correct for geometric distortion in MR images arising principally from gradient field non-linearity and magnet field inhomogeneity. The phantom was designed based on the concept that a point in space can be defined using three orthogonal planes. This novel design approach allows for as many control points as desired. Employing this novel design, a highly accurate method has been developed that enables the positions of the control points to be measured to sub-voxel accuracy. The phantom described in this paper was constructed to fit into a body coil of a MRI scanner, (external dimensions of the phantom were: 310 mm x 310 mm x 310 mm), and it contained 10,830 control points. With this phantom, the mean errors in the measured coordinates of the control points were on the order of 0.1 mm or less, which were less than one tenth of the voxel's dimensions of the phantom image. The calculated three-dimensional distortion map, i.e., the differences between the image positions and true positions of the control points, can then be used to compensate for geometric distortion for a full image restoration. It is anticipated that this novel method will have an impact on the applicability of MRI in both clinical and research settings. especially in areas where geometric accuracy is highly required, such as in MR neuro-imaging. (C) 2004 Elsevier Inc. All rights reserved.

Genetic algorithm optimization of adaptive multi-scale GLCM features

We introduce a new second-order method of texture analysis called Adaptive Multi-Scale Grey Level Co-occurrence Matrix (AMSGLCM), based on the well-known Grey Level Co-occurrence Matrix (GLCM) method. The method deviates significantly from GLCM in that features are extracted, not via a fixed 2D weighting function of co-occurrence matrix elements, but by a variable summation of matrix elements in 3D localized neighborhoods. We subsequently present a new methodology for extracting optimized, highly discriminant features from these localized areas using adaptive Gaussian weighting functions. Genetic Algorithm (GA) optimization is used to produce a set of features whose classification worth is evaluated by discriminatory power and feature correlation considerations. We critically appraised the performance of our method and GLCM in pairwise classification of images from visually similar texture classes, captured from Markov Random Field (MRF) synthesized, natural, and biological origins. In these cross-validated classification trials, our method demonstrated significant benefits over GLCM, including increased feature discriminatory power, automatic feature adaptability, and significantly improved classification performance.

Fourier-domain optical coherence tomography: optimization of signal-to-noise ratio in full space

Optical coherence tomography (OCT) is an emerging coherence-domain technique capable of in vivo imaging of sub-surface structures at millimeter-scale depth. Its steady progress over the last decade has been galvanized by a breakthrough detection concept, termed spectral-domain OCT, which has resulted in a dramatic improvement of the OCT signal-to-noise ratio of 150 times demonstrated for weakly scattering objects at video-frame-rates. As we have realized, however, an important OCT sub-system remains sub-optimal: the sample arm traditionally operates serially, i.e. in flying-spot mode. To realize the full-field image acquisition, a Fourier holography system illuminated with a swept-source is employed instead of a Michelson interferometer commonly used in OCT. The proposed technique, termed Fourier-domain OCT, offers a new leap in signal-to-noise ratio improvement, as compared to flying-spot OCT systems, and represents the main thrust of this paper. Fourier-domain OCT is described, and its basic theoretical aspects, including the reconstruction algorithm, are discussed. (C) 2004 Elsevier B.V. All rights reserved.

Heat transfer and entropy generation optimization of forced convection in a porous-saturated duct of rectangular cross-section

We investigate analytically the first and the second law characteristics of fully developed forced convection inside a porous-saturated duct of rectangular cross-section. The Darcy-Brinkman flow model is employed. Three different types of thermal boundary conditions are examined. Expressions for the Nusselt number, the Bejan number, and the dimensionless entropy generation rate are presented in terms of the system parameters. The conclusions of this analytical study will make it possible to compare, evaluate, and optimize alternative rectangular duct design options in terms of heat transfer, pressure drop, and entropy generation. (c) 2006 Elsevier Ltd. All rights reserved.

Scalable Visualization of Galaxies, Oceans, and Brains

One of the challenges in scientific visualization is to generate software libraries suitable for the large-scale data emerging from tera-scale simulations and instruments. We describe the efforts currently under way at SDSC and NPACI to address these challenges. The scope of the SDSC project spans data handling, graphics, visualization, and scientific application domains. Components of the research focus on the following areas: intelligent data storage, layout and handling, using an associated “Floor-Plan” (meta data); performance optimization on parallel architectures; extension of SDSC’s scalable, parallel, direct volume renderer to allow perspective viewing; and interactive rendering of fractional images (“imagelets”), which facilitates the examination of large datasets. These concepts are coordinated within a data-visualization pipeline, which operates on component data blocks sized to fit within the available computing resources. A key feature of the scheme is that the meta data, which tag the data blocks, can be propagated and applied consistently. This is possible at the disk level, in distributing the computations across parallel processors; in “imagelet” composition; and in feature tagging. The work reflects the emerging challenges and opportunities presented by the ongoing progress in high-performance computing (HPC) and the deployment of the data, computational, and visualization Grids.

Seven retinal specializations in the tubular eye of the deep-sea pearleye, Scopelarchus michaelsarsi: A case study in visual optimization

The deep-sea pearleye, Scopelarchus michaelsarsi (Scopelarchidae) is a mesopelagic teleost with asymmetric or tubular eyes. The main retina subtends a large dorsal binocular field, while the accessory retina subtends a restricted monocular field of lateral visual space. Ocular specializations to increase the lateral visual field include an oblique pupil and a corneal lens pad. A detailed morphological and topographic study of the photoreceptors and retinal ganglion cells reveals seven specializations: a centronasal region of the main retina with ungrouped rod-like photoreceptors overlying a retinal tapetum; a region of high ganglion cell density (area centralis of 56.1x10(3) cells per mm(2)) in the centrolateral region of the main retina; a centrotemporal region of the main retina with grouped rod-like photoreceptors; a region (area giganto cellularis) of large (32.2+/-5.6 mu m(2)), alpha-like ganglion cells arranged in a regular array (nearest neighbour distance 53.5+/-9.3 mu m with a conformity ratio of 5.8) in the temporal main retina; an accessory retina with grouped rod-like photoreceptors; a nasotemporal band of a mixture of rod-and cone-like photoreceptors restricted to the ventral accessory retina; and a retinal diverticulum comprised of a ventral region of differentiated accessory retina located medial to the optic nerve head. Retrograde labelling from the optic nerve with DiI shows that approximately 14% of the cells in the ganglion cell layer of the main retina are displaced amacrine cells at 1.5 mm eccentricity. Cryosectioning of the tubular eye confirms Matthiessen's ratio (2.59), and calculations of the spatial resolving power suggests that the function of the area centralis (7.4 cycles per degree/8.1 minutes of are) and the cohort of temporal alpha-like ganglion cells (0.85 cycles per degree/70.6 minutes of are) in the main retina may be different. Low summation ratios in these various retinal zones suggests that each zone may mediate distinct visual tasks in a certain region of the visual field by optimizing sensitivity and/or resolving power.

Analysis of small signal stability margins using genetic optimization

Power system small signal stability analysis aims to explore different small signal stability conditions and controls, namely: (1) exploring the power system security domains and boundaries in the space of power system parameters of interest, including load flow feasibility, saddle node and Hopf bifurcation ones; (2) finding the maximum and minimum damping conditions; and (3) determining control actions to provide and increase small signal stability. These problems are presented in this paper as different modifications of a general optimization to a minimum/maximum, depending on the initial guesses of variables and numerical methods used. In the considered problems, all the extreme points are of interest. Additionally, there are difficulties with finding the derivatives of the objective functions with respect to parameters. Numerical computations of derivatives in traditional optimization procedures are time consuming. In this paper, we propose a new black-box genetic optimization technique for comprehensive small signal stability analysis, which can effectively cope with highly nonlinear objective functions with multiple minima and maxima, and derivatives that can not be expressed analytically. The optimization result can then be used to provide such important information such as system optimal control decision making, assessment of the maximum network's transmission capacity, etc. (C) 1998 Elsevier Science S.A. All rights reserved.

Perceptual quality metrics applied to still image compression

We present a review of perceptual image quality metrics and their application to still image compression. The review describes how image quality metrics can be used to guide an image compression scheme and outlines the advantages, disadvantages and limitations of a number of quality metrics. We examine a broad range of metrics ranging from simple mathematical measures to those which incorporate full perceptual models. We highlight some variation in the models for luminance adaptation and the contrast sensitivity function and discuss what appears to be a lack of a general consensus regarding the models which best describe contrast masking and error summation. We identify how the various perceptual components have been incorporated in quality metrics, and identify a number of psychophysical testing techniques that can be used to validate the metrics. We conclude by illustrating some of the issues discussed throughout the paper with a simple demonstration. (C) 1998 Elsevier Science B.V. All rights reserved.

Bandwidth considerations for multilevel converters

Multilevel converters can achieve an overall effective switch frequency multiplication and consequent ripple reduction through the cancellation of the lowest order switch frequency terms. This paper investigates the harmonic content and the frequency response of these multimodulator converters. It is shown that the transfer function of uniformly sampled modulators is a bessel function associated with the inherent sampling process. Naturally sampled modulators have a flat transfer function, but multiple switchings per switch cycle will occur unless the input is slew-rate limited. Lower sideband harmonics of the effective carrier frequency and, in uniform converters, harmonics of the input signal also limit the useful bandwidth. Observations about the effect of the number of converters, their type (naturally or uniformly sampled), and the ratio of modulating frequency and switch frequency are made.

Simulation and optimization of heated, inviscid flows in scramjet ducts

A space-marching code for the simulation and optimization of inviscid supersonic flow in three dimensions is described. The now in a scramjet module with a relatively complex three-dimensional geometry is examined and wall-pressure estimates are compared with experimental data. Given that viscous effects are not presently included, the comparison is reasonable. The thermodynamic compromise of adding heat in a diverging combustor is also examined. The code is then used to optimize the shape of a thrust surface for a simpler (box-section) scramjet module in the presence of uniform and nonuniform heat distributions. The optimum two-dimensional profiles for the thrust surface are obtained via a perturbation procedure that requires about 30-50 now solutions. It is found that the final shapes are fairly insensitive to the details of the heat distribution.

Remotely sensed estimates of vegetation structural characteristics in restored wetlands, Southern California

Traditional field sampling approaches for ecological studies of restored habitat can only cover small areas in detail, con be time consuming, and are often invasive and destructive. Spatially extensive and non-invasive remotely sensed data can make field sampling more focused and efficient. The objective of this work was to investigate the feasibility and accuracy of hand-held and airborne remotely sensed data to estimate vegetation structural parameters for an indicator plant species in a restored wetland. High spatial resolution, digital, multispectral camera images were captured from an aircraft over Sweetwater Marsh (San Diego County, California) during each growing season between 1992-1996. Field data were collected concurrently, which included plant heights, proportional ground cover and canopy architecture type, and spectral radiometer measurements. Spartina foliosa (Pacific cordgrass) is the indicator species for the restoration monitoring. A conceptual model summarizing the controls on the spectral reflectance properties of Pacific cordgrass was established. Empirical models were developed relating the stem length, density, and canopy architecture of cordgrass to normalized-difference-vegetation-index values. The most promising results were obtained from empirical estimates of total ground cover using image data that had been stratified into high, middle, and low marsh zones. As part of on-going restoration monitoring activities, this model is being used to provide maps of estimated vegetation cover.