Classification of Material Mixtures in Volume Data for Visualization and Modeling

Material classification is a key stop in creating computer graphics models and images from volume data, We present a new algorithm for identifying the distribution of different material types in volumetric datasets such as those produced with Magnetic Resonance Imaging (NMI) or Computed Tomography (CT). The algorithm assumes that voxels can contain more than one material, e.g. both muscle and fat; we wish to compute the relative proportion of each material in the voxels. Other classification methods have utilized Gaussian probability density functions to model the distribution of values within a dataset. These Gaussian basis functions work well for voxels with unmixed materials, but do not work well where the materials are mixed together. We extend this approach by deriving non-Gaussian "mixture" basis functions. We treat a voxel as a volume, not as a single point. We use the distribution of values within each voxel-sized volume to identify materials within the voxel using a probabilistic approach. The technique reduces the classification artifacts that occur along boundaries between materials. The technique is useful for making higher quality geometric models and renderings from volume data, and has the potential to make more accurate volume measurements. It also classifies noisy, low-resolution data well

Partial-volume Bayesian classification of material mixtures in MR volume data using voxel histograms

The authors present a new algorithm for identifying the distribution of different material types in volumetric datasets such as those produced with magnetic resonance imaging (MRI) or computed tomography (CT). Because the authors allow for mixtures of materials and treat voxels as regions, their technique reduces errors that other classification techniques can create along boundaries between materials and is particularly useful for creating accurate geometric models and renderings from volume data. It also has the potential to make volume measurements more accurately and classifies noisy, low-resolution data well. There are two unusual aspects to the authors' approach. First, they assume that, due to partial-volume effects, or blurring, voxels can contain more than one material, e.g., both muscle and fat; the authors compute the relative proportion of each material in the voxels. Second, they incorporate information from neighboring voxels into the classification process by reconstructing a continuous function, ρ(x), from the samples and then looking at the distribution of values that ρ(x) takes on within the region of a voxel. This distribution of values is represented by a histogram taken over the region of the voxel; the mixture of materials that those values measure is identified within the voxel using a probabilistic Bayesian approach that matches the histogram by finding the mixture of materials within each voxel most likely to have created the histogram. The size of regions that the authors classify is chosen to match the sparing of the samples because the spacing is intrinsically related to the minimum feature size that the reconstructed continuous function can represent

Pure phase-encoded MRI and classification of solids

Here, the authors combine a pure phase-encoded magnetic resonance imaging (MRI) method with a new tissue-classification technique to make geometric models of a human tooth. They demonstrate the feasibility of three-dimensional imaging of solids using a conventional 11.7-T NMR spectrometer. In solid-state imaging, confounding line-broadening effects are typically eliminated using coherent averaging methods. Instead, the authors circumvent them by detecting the proton signal at a fixed phase-encode time following the radio-frequency excitation. By a judicious choice of the phase-encode time in the MRI protocol, the authors differentiate enamel and dentine sufficiently to successfully apply a new classification algorithm. This tissue-classification algorithm identifies the distribution of different material types, such as enamel and dentine, in volumetric data. In this algorithm, the authors treat a voxel as a volume, not as a single point, and assume that each voxel may contain more than one material. They use the distribution of MR image intensities within each voxel-sized volume to estimate the relative proportion of each material using a probabilistic approach. This combined approach, involving MRI and data classification, is directly applicable to bone imaging and hard-tissue contrast-based modeling of biological solids

The stransverse mass, MT2, in special cases

This document describes some special cases in which the stransverse mass, MT2, may be calculated by non-iterative algorithms. The most notable special case is that in which the visible particles and the hypothesised invisible particles are massless -- a situation relevant to its current usage in the Large Hadron Collider as a discovery variable, and a situation for which no analytic answer was previously known. We also derive an expression for MT2 in another set of new (though arguably less interesting) special cases in which the missing transverse momentum must point parallel or anti parallel to the visible momentum sum. In addition, we find new derivations for already known MT2 solutions in a manner that maintains manifest contralinear boost invariance throughout, providing new insights into old results. Along the way, we stumble across some unexpected results and make conjectures relating to geometric forms of M_eff and H_T and their relationship to MT2.Comment: 11 pages, no figures. v2 corrects minor typos. v3 corrects an incorrect statement in footnote 8 and inserts a missing term in eq (3.9). v4 and v5 correct minor typos spotted by reader

COMPTEL upper limits for Seyfert galaxies

The gamma‐ray emission of Seyfert galaxies has fallen far short of pre‐GRO expectations. No single object of this class has been detected by either COMPTEL or EGRET, and OSSE has detected only a fraction of the Seyferts expected. To derive a more stringent upper limit to the emission from these objects in the energy ranges 0.75 to 1 and 1 to 3 MeV, we have summed a large number of COMPTEL observations acquired during Phase 1 of the GRO mission. From a total of 47 observations of 23 individual X‐ray selected Seyfert galaxies, we derive preliminary upper limits of 8×10−8 photons/(cm2 s keV) in the 0.75‐1 MeV band and 1×10−8 photons/(cm2 s keV) in the 1‐3 MeV band

Human fur gene encodes a yeast KEX2-like endoprotease that cleaves pro-beta-NGF in vivo.

Extracts from BSC-40 cells infected with vaccinia recombinants expressing either the yeast KEX2 prohormone endoprotease or a human structural homologue (fur gene product) contained an elevated level of a membrane-associated endoproteolytic activity that could cleave at pairs of basic amino acids (-LysArg- and -ArgArg-). The fur-directed activity (furin) shared many properties with Kex2p including activity at pH 7.3 and a requirement for calcium. By using antifurin antibodies, immunoblot analysis detected two furin translation products (90 and 96 kD), while immunofluorescence indicated localization to the Golgi apparatus. Coexpression of either Kex2p or furin with the mouse beta-nerve growth factor precursor (pro-beta-NGF) resulted in greatly enhanced conversion of the precursor to mature nerve growth factor. Thus, the sequence homology shared by furin and the yeast KEX2 prohormone processing enzyme is reflected by significant functional homology both in vitro and in vivo

The Canadian Nonprofit and Voluntary Sector in Comparative Perspective

The Johns Hopkins Comparative Nonprofit Sector Project aims to close the gaps in basic knowledge about the nonprofit or civil society sector and to shed light on the reasons for the significant disparities that exist in the size, composition, financing and role of the sector in various countries and regions. This report presents the major descriptive findings of this work in Canada and compares them to results from 36 countries covered by this project. It also outlines the major historical developments that shaped the contours of the sector and discusses legal and political issues faced by the sector today

The X-ray Spectrum of the Rapid Burster using the Chandra HETGS

We present observations of the Rapid Burster (RB, also known as MXB 1730-335) using the Chandra High Energy Transmission Grating Spectrometer. The average interval between type II (accretion) bursts was about 40 s. There was one type I (thermonuclear flash) burst and about 20 "mini-bursts" which are probably type II bursts whose peak flux is 10-40% of the average peak flux of the other type II bursts. The time averaged spectra of the type II bursts are well fit by a blackbody with a temperature of kT = 1.6 keV, a radius of 8.9 km for a distance of 8.6 kpc, and an interstellar column density of 1.7e22 per sq. cm. No narrow emission or absorption lines were clearly detected. The 3 sigma upper limits to the equivalent widths of any features are < 10 eV in the 1.1-7.0 keV band and as small as 1.5 eV near 1.7 keV. We suggest that Comptonization destroys absorption features such as the resonance line of Fe XXVI.Comment: 10 pages, 4 figures, accepted for publication in AJ (with minor changes and enhanced discussion of the instrument configuration

Individual Differences in Emotion Expression: Hierarchical Structure and Relations with Psychological Distress

Several constructs reflecting individual differences in emotion expression have been described in the literature, yet their structural organization is unknown. The present study provided a taxonomy of these individual differences and determined their relations to depression and anxiety symptoms. Exploratory factor analyses suggested seven emotion-expression factors-Affect Intensity, Ambivalence About Expression Disclosure of Negative Emotion, Disclosure of Emotion, Disclosure of Lack of Affect, Expression of Positive Emotion, and Secret Keeping-are explained by two second-order factors: Emotional Constraint and Emotional Expression. Multiple regression and canonical correlation analyses suggested that a reluctance to express emotions is related to heightened psychological symptoms. These findings bridge constructs from disparate literatures, and they provide support for emotion dysregulation models of affective disorders

Automated visual tracking for studying the ontogeny of zebrafish swimming

The zebrafish Danio rerio is a widely used model organism in studies of genetics, developmental biology, and recently, biomechanics. In order to quantify changes in swimming during all stages of development, we have developed a visual tracking system that estimates the posture of fish. Our current approach assumes planar motion of the fish, given image sequences taken from a top view. An accurate geometric fish model is automatically designed and fit to the images at each time frame. Our approach works across a range of fish shapes and sizes and is therefore well suited for studying the ontogeny of fish swimming, while also being robust to common environmental occlusions. Our current analysis focuses on measuring the influence of vertebra development on the swimming capabilities of zebrafish. We examine wild-type zebrafish and mutants with stiff vertebrae (stocksteif) and quantify their body kinematics as a function of their development from larvae to adult (mutants made available by the Hubrecht laboratory, The Netherlands). By tracking the fish, we are able to measure the curvature and net acceleration along the body that result from the fish's body wave. Here, we demonstrate the capabilities of the tracking system for the escape response of wild-type zebrafish and stocksteif mutant zebrafish. The response was filmed with a digital high-speed camera at 1500 frames s–1. Our approach enables biomechanists and ethologists to process much larger datasets than possible at present. Our automated tracking scheme can therefore accelerate insight in the swimming behavior of many species of (developing) fish