Thermal/fluid characteristics of 3-D woven mesh structures as heat exchanger surfaces

The present work demonstrates the fabrication methodology of a three-dimensional (3-D), aluminum wire filament, bonded mesh deployed as a heat exchange surface. A model of the effective thermal conductivity of the mesh is developed. Apparatus to measure the coolant pressure-drop and heat transfer coefficient are described. Measurements are reported for fabricated test samples of varying thickness. Mesh Stanton number and friction factor correlations for a coolant with Prandtl number equal to 9.5 (chilled water) are reported. A heat exchanger performance evaluation, comparing the 3-D woven mesh technology to another exchanger surface technology, is described. We have found that the weaving/wire bonding process must be carefully controlled to insure that target porosity, specific surface area and effective thermal conductivity are achieved. Effective thermal conductivities are found to be at least two-times larger than achieved in other comparable porous media configurations. Mesh friction factor and Stanton number are comparable to those achieved with other exchanger surface technologies. The exchanger performance comparison shows that exchangers having superior performance can be configured.     

New approach to extract phase feature of 3-D objects by wavelength-scanning digital holography

Phaseinformationisoneofkeyfeaturesfor3Dob jectsespeciallyforalmosttransparentobject,suchas somebiologicaltissues.Thus,phasefeaturesaremost widelyappliedinrecognization,opticalmetrologyandsoon.Somemethodshavebeenproposedtoobtainthe phaseinformation[14]ofa3…     

B-spline explicit active surfaces: an efficient framework for real-time 3-D region-based segmentation

A new formulation of active contours based on explicit functions has been recently suggested. This novel framework allows real-time 3-D segmentation since it reduces the dimensionality of the segmentation problem. In this paper, we propose a B-spline formulation of this approach, which further improves the computational efficiency of the algorithm. We also show that this framework allows evolving the active contour using local region-based terms, thereby overcoming the limitations of the original method while preserving computational speed. The feasibility of real-time 3-D segmentation is demonstrated using simulated and medical data such as liver computer tomography and cardiac ultrasound images.     

Finite-element method modeling of superconductors: from 2-D to 3-D

A three-dimensional (3-D) numerical modeling technique for solving problems involving superconducting materials is presented. The model is implemented in finite-element method software and is based on a recently developed 3-D formulation for general electromagnetic problems with solid conductors. It has been adapted for modeling of superconductors with nonlinear resistivity in 3-D, characterized by a power-law E-J relation. It has first been compared with an existing and verified two-dimensional (2-D) model: Compared are the current density distribution inside the conductors and the self-field ac losses for different applied transport currents. Second, the model has been tested for computing the current distribution with typical 3-D geometries, such as corner-shaped and twisted superconductors. Finally, it has been used with two superconducting filaments in the presence of external magnetic field for verifying the existence of coupling currents. This effect deals with the finite length of the conductors and cannot be taken into account by 2-D models.     

Deformable triangular surfaces using fast 1-D radial Lagrangian dynamics--segmentation of 3-D MR and CT images of the wrist

We developed a new triangulated deformable surface model, which is used to detect the boundary of the bones in three-dimensional magnetic resonance (MR) and computed tomography (CT) images of the wrist. This surface model is robust to initialization and provides wide geometrical coverage and quantitative power. The surface is deformed by applying one-dimensional (1-D) radial Lagrangian dynamics. For initialization a tetrahedron is placed within the bone to be segmented. This initial surface is inflated to a binary approximation of the boundary. During inflation, the surface is refined by the addition of vertices. After the surface is fully inflated, a detailed, accurate boundary detection is obtained by the application of radial scale-space relaxation. In this optimization stage, the image intensity is filtered with a series of 1-D second-order Gaussian filters. The resolution of the triangulated mesh is adapted to the width of the Gaussian filter. To maintain the coherence between the vertices, a resampling technique is applied which is based on collapsing and splitting of edges. We regularized the triangulated mesh by a combination of volume-preserving vertex averaging and equi-angulation of edges. In this paper, we present both qualitative and quantitative results of the surface segmentations in eight MR and ten CT images.     

Segmenting and tracking fluorescent cells in dynamic 3-D microscopy with coupled active surfaces.

Cell migrations and deformations play essential roles in biological processes, such as parasite invasion, immune response, embryonic development, and cancer. We describe a fully automatic segmentation and tracking method designed to enable quantitative analyses of cellular shape and motion from dynamic three-dimensional microscopy data. The method uses multiple active surfaces with or without edges, coupled by a penalty for overlaps, and a volume conservation constraint that improves outlining of cell/cell boundaries. Its main advantages are robustness to low signal-to-noise ratios and the ability to handle multiple cells that may touch, divide, enter, or leave the observation volume. We give quantitative validation results based on synthetic images and show two examples of applications to real biological data.     

Semiautomatic 3-D image registration as applied to interventional MRI liver cancer treatment

We evaluated semiautomatic, voxel-based registration methods for a new application, the assessment and optimization of interventional magnetic resonance imaging (I-MRI) guided thermal ablation of liver cancer. The abdominal images acquired on a low-field-strength, open I-MRI system contain noise, motion artifacts, and tissue deformation. Dissimilar images can be obtained as a result of different MRI acquisition techniques and/or changes induced by treatments. These features challenge a registration algorithm. We evaluated one manual and four automated methods on clinical images acquired before treatment, immediately following treatment, and during several follow-up studies. Images were T2-weighted, T1-weighted Gd-DTPA enhanced, T1-weighted, and short-inversion-time inversion recovery (STIR). Registration accuracy was estimated from distances between anatomical landmarks. Mutual information gave better results than entropy, correlation, and variance of gray-scale ratio. Preprocessing steps such as masking and an initialization method that used two-dimensional (2-D) registration to obtain initial transformation estimates were crucial. With proper preprocessing, automatic registration was successful with all image pairs having reasonable image quality. A registration accuracy of approximately equal to 3 mm was achieved with both manual and mutual information methods. Despite motion and deformation in the liver, mutual information registration is sufficiently accurate and robust for useful applications in I-MRI thermal ablation therapy.     

3-D/2-D registration of CT and MR to X-ray images

A crucial part of image-guided therapy is registration of preoperative and intraoperative images, by which the precise position and orientation of the patient's anatomy is determined in three dimensions. This paper presents a novel approach to register three-dimensional (3-D) computed tomography (CT) or magnetic resonance (MR) images to one or more two-dimensional (2-D) X-ray images. The registration is based solely on the information present in 2-D and 3-D images. It does not require fiducial markers, intraoperative X-ray image segmentation, or timely construction of digitally reconstructed radiographs. The originality of the approach is in using normals to bone surfaces, preoperatively defined in 3-D MR or CT data, and gradients of intraoperative X-ray images at locations defined by the X-ray source and 3-D surface points. The registration is concerned with finding the rigid transformation of a CT or MR volume, which provides the best match between surface normals and back projected gradients, considering their amplitudes and orientations. We have thoroughly validated our registration method by using MR, CT, and X-ray images of a cadaveric lumbar spine phantom for which "gold standard" registration was established by means of fiducial markers, and its accuracy assessed by target registration error. Volumes of interest, containing single vertebrae L1-L5, were registered to different pairs of X-ray images from different starting positions, chosen randomly and uniformly around the "gold standard" position. CT/X-ray (MR/ X-ray) registration, which is fast, was successful in more than 91% (82% except for L1) of trials if started from the "gold standard" translated or rotated for less than 6 mm or 17 degrees (3 mm or 8.6 degrees), respectively. Root-mean-square target registration errors were below 0.5 mm for the CT to X-ray registration and below 1.4 mm for MR to X-ray registration.     

A generalization of the octonion Fourier transform to 3-D octonion-valued signals: properties and possible applications to 3-D LTI partial differential systems

Multidimensional Systems and Signal Processing - The paper is devoted to the development of the octonion Fourier transform (OFT) theory initiated in 2011 in articles by Hahn and Snopek. It is also...     

Using 1-D Models to Interpret the Reflectance Anisotropy of 3-D Canopy Targets: Issues and Caveats

This paper evaluates 1) to what extent one-dimensional (1-D) models can be used to represent the magnitude and directionality of the surface reflectance field of heterogeneous canopy targets at different spatial resolutions, and 2) whether this usage results in significant biases in the estimation of the corresponding state variables. It will be seen that when both the 1-D and three-dimensional (3-D) models account for all features of the measured radiation field, then—in the absence of further information regarding the nature and structure of the target—the use of a 3-D model may amount to an over-interpretation of the available data. The simplified surface structure formulation contained within the 1-D model, on the other hand, may affect the values of the state variables that such models will retrieve. This is because the shape of the reflectance anisotropy of the 3-D target is almost always different from that of a structurally homogeneous (1-D) canopy with the same state variable values but no foliage clumping. By consequence the 1-D canopies that are capable of mimicking the bell (or bowl) shaped reflectance anisotropy of 3-D targets will tend to feature lower leaf area index, higher soil albedo and, in particular, predominantly erectophile (or plagiophile) leaf normal distributions.     

Principal curves for lumen center extraction and flow channel width estimation in 3-D arterial networks: theory, algorithm, and validation

We present an energy-minimization-based framework for locating the centerline and estimating the width of tubelike objects from their structural network with a nonparametric model. The nonparametric representation promotes simple modeling of nested branches and n -way furcations, i.e., structures that abound in an arterial network, e.g., a cerebrovascular circulation. Our method is capable of extracting the entire vascular tree from an angiogram in a single execution with a proper initialization. A succinct initial model from the user with arterial network inlets, outlets, and branching points is sufficient for complex vasculature. The novel method is based upon the theory of principal curves. In this paper, theoretical extension to grayscale angiography is discussed, and an algorithm to find an arterial network as principal curves is also described. Quantitative validation on a number of simulated data sets, synthetic volumes of 19 BrainWeb vascular models, and 32 Rotterdam Coronary Artery volumes was conducted. We compared the algorithm to a state-of-the-art method and further tested it on two clinical data sets. Our algorithmic outputs-lumen centers and flow channel widths-are important to various medical and clinical applications, e.g., vasculature segmentation, registration and visualization, virtual angioscopy, and vascular atlas formation and population study.     

Least-Square NUFFT Methods Applied to 2-D and 3-D Radially Encoded MR Image Reconstruction

Radially encoded MRI has gained increasing attention due to its motion insensitivity and reduced artifacts. However, because its samples are collected nonuniformly in the $k$-space, multidimensional (especially 3-D) radially sampled MRI image reconstruction is challenging. The objective of this paper is to develop a reconstruction technique in high dimensions with on-the-fly kernel calculation. It implements general multidimensional nonuniform fast Fourier transform (NUFFT) algorithms and incorporates them into a $k$-space image reconstruction framework. The method is then applied to reconstruct from the radially encoded $k$-space data, although the method is applicable to any non-Cartesian patterns. Performance comparisons are made against the conventional Kaiser–Bessel (KB) gridding method for 2-D and 3-D radially encoded computer-simulated phantoms and physically scanned phantoms. The results show that the NUFFT reconstruction method has better accuracy–efficiency tradeoff than the KB gridding method when the kernel weights are calculated on the fly. It is found that for a particular conventional kernel function, using its corresponding deapodization function as a scaling factor in the NUFFT framework has the potential to improve accuracy. In particular, when a cosine scaling factor is used, the NUFFT method is faster than KB gridding method since a closed-form solution is available and is less computationally expensive than the KB kernel (KB griding requires computation of Bessel functions). The NUFFT method has been successfully applied to 2-D and 3-D in vivo studies on small animals.      

Robust Gradient-Based 3-D/2-D Registration of CT and MR to X-Ray Images

One of the most important technical challenges in image-guided intervention is to obtain a precise transformation between the intrainterventional patient's anatomy and corresponding preinterventional 3-D image on which the intervention was planned. This goal can be achieved by acquiring intrainterventional 2-D images and matching them to the preinterventional 3-D image via 3-D/2-D image registration. A novel 3-D/2-D registration method is proposed in this paper. The method is based on robustly matching 3-D preinterventional image gradients and coarsely reconstructed 3-D gradients from the intrainterventional 2-D images. To improve the robustness of finding the correspondences between the two sets of gradients, hypothetical correspondences are searched for along normals to anatomical structures in 3-D images, while the final correspondences are established in an iterative process, combining the robust random sample consensus algorithm (RANSAC) and a special gradient matching criterion function. The proposed method was evaluated using the publicly available standardized evaluation methodology for 3-D/2-D registration, consisting of 3-D rotational X-ray, computed tomography, magnetic resonance (MR), and 2-D X-ray images of two spine segments, and standardized evaluation criteria. In this way, the proposed method could be objectively compared to the intensity, gradient, and reconstruction-based registration methods. The obtained results indicate that the proposed method performs favorably both in terms of registration accuracy and robustness. The method is especially superior when just a few X-ray images and when MR preinterventional images are used for registration, which are important advantages for many clinical applications.      

Multiple-incidence and multifrequency for profile reconstruction of random rough surfaces using the 3-D electromagnetic fast multipole model

A fast algorithm for reconstructing the profile of random rough surfaces using electromagnetic scattering data is presented. The algorithm is based on merging a fast forward solver and an efficient optimization technique. The steepest descent fast multipole method is used as the three-dimensional fast forward solver. A rapidly convergent descent method employing a "marching-on" strategy for processing multifrequency and multi-incidence angle data is introduced to minimize an underlying cost function. The cost function represents the error between true (synthetic) and simulated scattered field data. Several key issues that impact the accuracy in reconstructing the rough profile are examined in this work, e.g., the location and number of receivers, the incident and scattered directions, the surface roughness, and details regarding the manner in which sensitivity information is computed in the inversion scheme. The results show that using the multiple-incidence (one angle at a time) and the multifrequency (one frequency at a time) strategies lead to improve the profile reconstruction.     

3-D photonic-crystal heterostructures: fabrication and in-line resonator

A heterostructured photonic-crystal functional chip consisting of a resonator and waveguides is fabricated by a simple "autocloning" process. First, we prepare a substrate with different corrugation patterns by electron beam lithography and dry etching, and Ta/sub 2/O/sub 5/-SiO/sub 2/ multilayers are successively formed upon the substrate. An in-line resonator is fabricated and characterized by fiber-in-fiber-out measurement, and a resonance peak with Q=270 is demonstrated. The future outlook for the technology is also discussed.     

Recent developments to the MICHELLE 2-D/3-D electron gun and collector modeling code

Recent developments to the MICHELLE electron gun and collector design tool are reported in this paper. The MICHELLE code is a new finite-element (FE) two-dimensional and three-dimensional electrostatic particle-in-cell code that has been designed to address the recent beam optics modeling and simulation requirements for vacuum electron devices, ion sources, and charged-particle transport. Problem classes specifically targeted include depressed collectors, gridded-guns, multibeam guns, sheet-beam guns, and ion thrusters. The focus of the development program is to combine modern FE techniques with improved physics models. The code employs a conformal mesh, including both structured and unstructured mesh architectures for meshing flexibility, along with a new method for accurate, efficient particle tracking. New particle emission models for thermionic beam representation are included that support primary emission, with an advanced secondary emission model. This paper reports on three significant advances to MICHELLE over the past year; hybrid structured/unstructured mesh support, a time-domain electrostatic algorithm, and an ion plasma model with charge exchange.     

3-D SPECT simulations of a complex 3-D mathematical brain model: effects of 3-D geometric detector response, attenuation, scatter, and statistical noise

The quantitative imaging characteristics of ultrahigh-resolution parallel-hole SPECT, including 3-D geometric detector response, attenuation, scatter, and statistical noise, were investigated by simulations based on a complex digitized 3-D brain model of the gray and white matter distributions. The projection data resulting from a uniform distribution of gray and white matter radioactivity, in a ratio of 5:1, were simulated. The results demonstrate significant qualitative and quantitative artifacts in reconstructed human brain images. In the absence of attenuation, scatter, and noise, artifactual variation caused inaccuracies in regional radioactivity quantification. Inclusion of attenuation scatter, and noise in the simulation caused additional artifacts, and resulted in reconstructed images which qualitatively and quantitatively corresponded very closely to reconstructed images of the actual 3-D brain phantom which was constructed from the same set of data as the mathematical 3-D brain model. It is concluded that the major degrading factor in SPECT neuroimaging is the 3-D geometric detector response function.