66 resultados para image feature extraction


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In the context of cancer diagnosis and treatment, we consider the problem of constructing an accurate prediction rule on the basis of a relatively small number of tumor tissue samples of known type containing the expression data on very many (possibly thousands) genes. Recently, results have been presented in the literature suggesting that it is possible to construct a prediction rule from only a few genes such that it has a negligible prediction error rate. However, in these results the test error or the leave-one-out cross-validated error is calculated without allowance for the selection bias. There is no allowance because the rule is either tested on tissue samples that were used in the first instance to select the genes being used in the rule or because the cross-validation of the rule is not external to the selection process; that is, gene selection is not performed in training the rule at each stage of the cross-validation process. We describe how in practice the selection bias can be assessed and corrected for by either performing a cross-validation or applying the bootstrap external to the selection process. We recommend using 10-fold rather than leave-one-out cross-validation, and concerning the bootstrap, we suggest using the so-called. 632+ bootstrap error estimate designed to handle overfitted prediction rules. Using two published data sets, we demonstrate that when correction is made for the selection bias, the cross-validated error is no longer zero for a subset of only a few genes.

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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.

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Many images consist of two or more 'phases', where a phase is a collection of homogeneous zones. For example, the phases may represent the presence of different sulphides in an ore sample. Frequently, these phases exhibit very little structure, though all connected components of a given phase may be similar in some sense. As a consequence, random set models are commonly used to model such images. The Boolean model and models derived from the Boolean model are often chosen. An alternative approach to modelling such images is to use the excursion sets of random fields to model each phase. In this paper, the properties of excursion sets will be firstly discussed in terms of modelling binary images. Ways of extending these models to multi-phase images will then be explored. A desirable feature of any model is to be able to fit it to data reasonably well. Different methods for fitting random set models based on excursion sets will be presented and some of the difficulties with these methods will be discussed.

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Trust is a vital feature for Semantic Web: If users (humans and agents) are to use and integrate system answers, they must trust them. Thus, systems should be able to explain their actions, sources, and beliefs, and this issue is the topic of the proof layer in the design of the Semantic Web. This paper presents the design and implementation of a system for proof explanation on the Semantic Web, based on defeasible reasoning. The basis of this work is the DR-DEVICE system that is extended to handle proofs. A critical aspect is the representation of proofs in an XML language, which is achieved by a RuleML language extension.

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A method is presented for the direct extraction of the recombinant protein Long-R-3-IGF-I from inclusion bodies located in the cytoplasm of intact Escherichia coli cells. Chemical treatment with 6M urea, 3 mM EDTA, and 20 mM dithiothreitol (DTT) at pH 9.0 proved an effective combination for extracting recombinant protein from intact cells. Comparable levels of Long-R-3-IGF-I were recovered by direct extraction as achieved by in vitro dissolution following mechanical disruption. However, the purity of directly extracted recombinant protein was lower due to contamination by bacterial cell components. The kinetics of direct extraction are described using a first-order equation with the time constant of 3 min. Urea appears important for permeabilization of the cell and dissolution of the inclusion body. Conversely, EDTA is involved in permeabilization of the cell wall and DTT enhances protein release. pH proved to be important with lower levels of protein release achieved at low pH values (

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This communication describes an improved one-step solid-phase extraction method for the recovery of morphine (M), morphine-3-glucuronide (M3G), and morphine-6-glucuronide (M6G) from human plasma with reduced coextraction of endogenous plasma constituents, compared to that of the authors' previously reported method. The magnitude of the peak caused by endogenous plasma components in the chromatogram that eluted immediately before the retention time of M3G has been reduced (similar to 80%) significantly (p < 0.01) while achieving high extraction efficiencies for the compounds of interest, viz morphine, M6G, and M3G (93.8 +/- 2.5, 91.7 +/- 1.7, and 93.1 +/- 2.2%, respectively). Furthermore, when the improved solid-phase extraction method was used, the extraction cartridge-derived late-eluting peak (retention time 90 to 100 minutes) reported in our previous method, was no longer present in the plasma extracts. Therefore the combined effect of reducing the recovery of the endogenous components of plasma that chromatographed just before the retention time of M3G and the removal of the late-eluting, extraction cartridge-derived peak has resulted in a decrease in the chromatographic run-time to 20 minutes, thereby increasing the sample throughput by up to 100%.

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A new method of poly-beta-hydroxybutyrate (PHB) extraction from recombinant E. coli is proposed, using homogenization and centrifugation coupled with sodium hypochlorite treatment. The size of PHB granules and cell debris in homogenates was characterised as a function of the number of homogenization passes. Simulation was used to develop the PHB and cell debris fractionation system, enabling numerical examination of the effects of repeated homogenization and centrifuge-feedrate variation. The simulation provided a good prediction of experimental performance. Sodium hypochlorite treatment was necessary to optimise PHB fractionation. A PHB recovery of 80% at a purity of 96.5% was obtained with the final optimised process. Protein and DNA contained in the resultant product were negligible. The developed process holds promise for significantly reducing the recovery cost associated with PHB manufacture.

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A sensitive and reproducible solid-phase extraction (SPE) method for the quantification of oxycodone in human plasma was developed. Varian Certify SPE cartridges containing both C-8 and benzoic acid functional groups were the most suitable for the extraction of oxycodone and codeine (internal standard), with consistently high (greater than or equal to 80%) and reproducible recoveries. The elution mobile phase consisted of 1.2 ml of butyl chloride-isopropanol (80:20, v/v) containing 2% ammonia. The quantification limit for oxycodone was 5.3 pmol on-column. Within-day and inter-day coefficients of variation were 1.2% and 6.8% respectively for 284 nM oxycodone and 9.5% and 6.2% respectively for 28.4 nM oxycodone using 0.5-ml plasma aliquots. (C) 1998 Elsevier Science BN. All rights reserved.

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A simple method for the measurement of pindolol enantiomers by HPLC is presented. Alkalinized serum or urine is extracted with ethyl acetate and the residue remaining after evaporation of the organic layer is then derivatised with (S)-(-)-alpha-methylbenzyl isocyanate. The diastereoisomers of derivatised pindolol and metoprolol (internal standard) are separated by high-performance liquid chromatography (HPLC) using a C-18 silica column and detected using fluorescence (excitation lambda: 215 nm, emission lambda: 320 nm). The assay displays reproducible linearity for pindolol enantiomers with a correlation coefficient of r(2) greater than or equal to 0.998 over the concentration range 8-100 ng ml(-1) for plasma and 0.1-2.5 mu g ml(-1) for urine. The coefficient of variation for accuracy and precision of the quality control samples for both plasma and urine are consistently

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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.

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In previous parts of this study we developed procedures for the high-efficiency chemical extraction of soluble and insoluble protein from intact Escherichia coli cells. Although high yields were obtained, extraction of recombinant protein directly from cytoplasmic inclusion bodies led to low product purity due to coextraction of soluble contaminants. In this work, a two-stage procedure for the selective extraction of recombinant protein at high efficiency and high purity is reported. In the first stage, inclusion-body stability is promoted by the addition of 15 mM 2-hydroxyethyldisulfide (2-HEDS), also known as oxidized P-mercaptoethanol, to the permeabil ization buffer (6 M urea + 3 mM ethylenediaminetetra-acetate [EDTA]). 2-HEDS is an oxidizing agent believed to promote disulfide bond formation, rendering the inclusion body resistant to solubilization in 6 M urea. Contaminating proteins are separated from the inclusion-body fraction by centrifugation. in the second stage, disulfide bonds are readily eliminated by including reducing agent (20 mM dithiothreitol [DTT]) into the permeabilization buffer. Extraction using this selective two-stage process yielded an 81% (w/w) recovery of the recombinant protein Long-R-3-IGF-I from inclusion bodies located in the cytoplasm of intact E. coli, at a purity of 46% (w/w). This was comparable to that achieved by conventional extraction (mechanical disruption followed by centrifugation and solubilization). A pilot-scale procedure was also demonstrated using a stirred reactor and diafiltration. This is the first reported study that achieves both high extraction efficiency and selectivity by the chemical treatment of cytoplasmic inclusion bodies in intact bacterial cells. (C) 1999 John Wiley & Sons, Inc.

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An automated method for extracting brain volumes from three commonly acquired three-dimensional (3D) MR images (proton density, T1 weighted, and T2-weighted) of the human head is described. The procedure is divided into four levels: preprocessing, segmentation, scalp removal, and postprocessing. A user-provided reference point is the sole operator-dependent input required, The method's parameters were first optimized and then fixed and applied to 30 repeat data sets from 15 normal older adult subjects to investigate its reproducibility. Percent differences between total brain volumes (TBVs) for the subjects' repeated data sets ranged from .5% to 2.2%. We conclude that the method is both robust and reproducible and has the potential for wide application.