Tests with VHR images for the identification of olive trees and other fruit trees in the European Union

NASA Astrophysics Data System (ADS)

Masson, Josiane; Soille, Pierre; Mueller, Rick

2004-10-01

In the context of the Common Agricultural Policy (CAP) there is a strong interest of the European Commission for counting and individually locating fruit trees. An automatic counting algorithm developed by the JRC (OLICOUNT) was used in the past for olive trees only, on 1m black and white orthophotos but with limits in case of young trees or irregular groves. This study investigates the improvement of fruit tree identification using VHR images on a large set of data in three test sites, one in Creta (Greece; one in the south-east of France with a majority of olive trees and associated fruit trees, and the last one in Florida on citrus trees. OLICOUNT was compared with two other automatic tree counting, applications, one using the CRISP software on citrus trees and the other completely automatic based on regional minima (morphological image analysis). Additional investigation was undertaken to refine the methods. This paper describes the automatic methods and presents the results derived from the tests.

Fast Quantitative Susceptibility Mapping with L1-Regularization and Automatic Parameter Selection

PubMed Central

Bilgic, Berkin; Fan, Audrey P.; Polimeni, Jonathan R.; Cauley, Stephen F.; Bianciardi, Marta; Adalsteinsson, Elfar; Wald, Lawrence L.; Setsompop, Kawin

2014-01-01

Purpose To enable fast reconstruction of quantitative susceptibility maps with Total Variation penalty and automatic regularization parameter selection. Methods ℓ1-regularized susceptibility mapping is accelerated by variable-splitting, which allows closed-form evaluation of each iteration of the algorithm by soft thresholding and FFTs. This fast algorithm also renders automatic regularization parameter estimation practical. A weighting mask derived from the magnitude signal can be incorporated to allow edge-aware regularization. Results Compared to the nonlinear Conjugate Gradient (CG) solver, the proposed method offers 20× speed-up in reconstruction time. A complete pipeline including Laplacian phase unwrapping, background phase removal with SHARP filtering and ℓ1-regularized dipole inversion at 0.6 mm isotropic resolution is completed in 1.2 minutes using Matlab on a standard workstation compared to 22 minutes using the Conjugate Gradient solver. This fast reconstruction allows estimation of regularization parameters with the L-curve method in 13 minutes, which would have taken 4 hours with the CG algorithm. Proposed method also permits magnitude-weighted regularization, which prevents smoothing across edges identified on the magnitude signal. This more complicated optimization problem is solved 5× faster than the nonlinear CG approach. Utility of the proposed method is also demonstrated in functional BOLD susceptibility mapping, where processing of the massive time-series dataset would otherwise be prohibitive with the CG solver. Conclusion Online reconstruction of regularized susceptibility maps may become feasible with the proposed dipole inversion. PMID:24259479

Towards automatic planning for manufacturing generative processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

CALTON,TERRI L.

2000-05-24

Generative process planning describes methods process engineers use to modify manufacturing/process plans after designs are complete. A completed design may be the result from the introduction of a new product based on an old design, an assembly upgrade, or modified product designs used for a family of similar products. An engineer designs an assembly and then creates plans capturing manufacturing processes, including assembly sequences, component joining methods, part costs, labor costs, etc. When new products originate as a result of an upgrade, component geometry may change, and/or additional components and subassemblies may be added to or are omitted from themore » original design. As a result process engineers are forced to create new plans. This is further complicated by the fact that the process engineer is forced to manually generate these plans for each product upgrade. To generate new assembly plans for product upgrades, engineers must manually re-specify the manufacturing plan selection criteria and re-run the planners. To remedy this problem, special-purpose assembly planning algorithms have been developed to automatically recognize design modifications and automatically apply previously defined manufacturing plan selection criteria and constraints.« less

Fully automatic registration and segmentation of first-pass myocardial perfusion MR image sequences.

PubMed

Gupta, Vikas; Hendriks, Emile A; Milles, Julien; van der Geest, Rob J; Jerosch-Herold, Michael; Reiber, Johan H C; Lelieveldt, Boudewijn P F

2010-11-01

Derivation of diagnostically relevant parameters from first-pass myocardial perfusion magnetic resonance images involves the tedious and time-consuming manual segmentation of the myocardium in a large number of images. To reduce the manual interaction and expedite the perfusion analysis, we propose an automatic registration and segmentation method for the derivation of perfusion linked parameters. A complete automation was accomplished by first registering misaligned images using a method based on independent component analysis, and then using the registered data to automatically segment the myocardium with active appearance models. We used 18 perfusion studies (100 images per study) for validation in which the automatically obtained (AO) contours were compared with expert drawn contours on the basis of point-to-curve error, Dice index, and relative perfusion upslope in the myocardium. Visual inspection revealed successful segmentation in 15 out of 18 studies. Comparison of the AO contours with expert drawn contours yielded 2.23 ± 0.53 mm and 0.91 ± 0.02 as point-to-curve error and Dice index, respectively. The average difference between manually and automatically obtained relative upslope parameters was found to be statistically insignificant (P = .37). Moreover, the analysis time per slice was reduced from 20 minutes (manual) to 1.5 minutes (automatic). We proposed an automatic method that significantly reduced the time required for analysis of first-pass cardiac magnetic resonance perfusion images. The robustness and accuracy of the proposed method were demonstrated by the high spatial correspondence and statistically insignificant difference in perfusion parameters, when AO contours were compared with expert drawn contours. Copyright © 2010 AUR. Published by Elsevier Inc. All rights reserved.

Optimization and automation of quantitative NMR data extraction.

PubMed

Bernstein, Michael A; Sýkora, Stan; Peng, Chen; Barba, Agustín; Cobas, Carlos

2013-06-18

NMR is routinely used to quantitate chemical species. The necessary experimental procedures to acquire quantitative data are well-known, but relatively little attention has been applied to data processing and analysis. We describe here a robust expert system that can be used to automatically choose the best signals in a sample for overall concentration determination and determine analyte concentration using all accepted methods. The algorithm is based on the complete deconvolution of the spectrum which makes it tolerant of cases where signals are very close to one another and includes robust methods for the automatic classification of NMR resonances and molecule-to-spectrum multiplets assignments. With the functionality in place and optimized, it is then a relatively simple matter to apply the same workflow to data in a fully automatic way. The procedure is desirable for both its inherent performance and applicability to NMR data acquired for very large sample sets.

Fully automatic segmentation of femurs with medullary canal definition in high and in low resolution CT scans.

PubMed

Almeida, Diogo F; Ruben, Rui B; Folgado, João; Fernandes, Paulo R; Audenaert, Emmanuel; Verhegghe, Benedict; De Beule, Matthieu

2016-12-01

Femur segmentation can be an important tool in orthopedic surgical planning. However, in order to overcome the need of an experienced user with extensive knowledge on the techniques, segmentation should be fully automatic. In this paper a new fully automatic femur segmentation method for CT images is presented. This method is also able to define automatically the medullary canal and performs well even in low resolution CT scans. Fully automatic femoral segmentation was performed adapting a template mesh of the femoral volume to medical images. In order to achieve this, an adaptation of the active shape model (ASM) technique based on the statistical shape model (SSM) and local appearance model (LAM) of the femur with a novel initialization method was used, to drive the template mesh deformation in order to fit the in-image femoral shape in a time effective approach. With the proposed method a 98% convergence rate was achieved. For high resolution CT images group the average error is less than 1mm. For the low resolution image group the results are also accurate and the average error is less than 1.5mm. The proposed segmentation pipeline is accurate, robust and completely user free. The method is robust to patient orientation, image artifacts and poorly defined edges. The results excelled even in CT images with a significant slice thickness, i.e., above 5mm. Medullary canal segmentation increases the geometric information that can be used in orthopedic surgical planning or in finite element analysis. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Reflecting on non-reflective action: An exploratory think-aloud study of self-report habit measures

PubMed Central

Gardner, Benjamin; Tang, Vinca

2014-01-01

Objectives Within health psychology, habit – the tendency to enact action automatically as a learned response to contextual cues – is most commonly quantified using the ‘Self-Report Habit Index’, which assesses behavioural automaticity, or measures combining self-reported behaviour frequency and context stability. Yet, the use of self-report to capture habit has proven controversial. This study used ‘think-aloud’ methods to investigate problems experienced when completing these two measures. Design Cross-sectional survey with think-aloud study. Methods Twenty student participants narrated their thoughts while completing habit measures applied to four health-related behaviours (active commuting, unhealthy snacking, and one context-free and one context-specific variant of alcohol consumption). Data were coded using thematic analysis procedures. Results Problems were found in 10% of responses. Notable findings included participants lacking confidence in reporting automaticity, struggling to recall behaviour or cues, differing in interpretations of ‘commuting’, and misinterpreting items. Conclusions While most responses were unproblematic, and further work is needed to investigate habit self-reports among larger and more diverse samples, findings nonetheless question the sensitivity of the measures, and the conceptualization of habit underpinning common applications of them. We offer suggestions to minimize these problems. PMID:23869847

Markov random field based automatic image alignment for electron tomography.

PubMed

Amat, Fernando; Moussavi, Farshid; Comolli, Luis R; Elidan, Gal; Downing, Kenneth H; Horowitz, Mark

2008-03-01

We present a method for automatic full-precision alignment of the images in a tomographic tilt series. Full-precision automatic alignment of cryo electron microscopy images has remained a difficult challenge to date, due to the limited electron dose and low image contrast. These facts lead to poor signal to noise ratio (SNR) in the images, which causes automatic feature trackers to generate errors, even with high contrast gold particles as fiducial features. To enable fully automatic alignment for full-precision reconstructions, we frame the problem probabilistically as finding the most likely particle tracks given a set of noisy images, using contextual information to make the solution more robust to the noise in each image. To solve this maximum likelihood problem, we use Markov Random Fields (MRF) to establish the correspondence of features in alignment and robust optimization for projection model estimation. The resulting algorithm, called Robust Alignment and Projection Estimation for Tomographic Reconstruction, or RAPTOR, has not needed any manual intervention for the difficult datasets we have tried, and has provided sub-pixel alignment that is as good as the manual approach by an expert user. We are able to automatically map complete and partial marker trajectories and thus obtain highly accurate image alignment. Our method has been applied to challenging cryo electron tomographic datasets with low SNR from intact bacterial cells, as well as several plastic section and X-ray datasets.

Shaping electromagnetic waves using software-automatically-designed metasurfaces.

PubMed

Zhang, Qian; Wan, Xiang; Liu, Shuo; Yuan Yin, Jia; Zhang, Lei; Jun Cui, Tie

2017-06-15

We present a fully digital procedure of designing reflective coding metasurfaces to shape reflected electromagnetic waves. The design procedure is completely automatic, controlled by a personal computer. In details, the macro coding units of metasurface are automatically divided into several types (e.g. two types for 1-bit coding, four types for 2-bit coding, etc.), and each type of the macro coding units is formed by discretely random arrangement of micro coding units. By combining an optimization algorithm and commercial electromagnetic software, the digital patterns of the macro coding units are optimized to possess constant phase difference for the reflected waves. The apertures of the designed reflective metasurfaces are formed by arranging the macro coding units with certain coding sequence. To experimentally verify the performance, a coding metasurface is fabricated by automatically designing two digital 1-bit unit cells, which are arranged in array to constitute a periodic coding metasurface to generate the required four-beam radiations with specific directions. Two complicated functional metasurfaces with circularly- and elliptically-shaped radiation beams are realized by automatically designing 4-bit macro coding units, showing excellent performance of the automatic designs by software. The proposed method provides a smart tool to realize various functional devices and systems automatically.

StochKit2: software for discrete stochastic simulation of biochemical systems with events.

PubMed

Sanft, Kevin R; Wu, Sheng; Roh, Min; Fu, Jin; Lim, Rone Kwei; Petzold, Linda R

2011-09-01

StochKit2 is the first major upgrade of the popular StochKit stochastic simulation software package. StochKit2 provides highly efficient implementations of several variants of Gillespie's stochastic simulation algorithm (SSA), and tau-leaping with automatic step size selection. StochKit2 features include automatic selection of the optimal SSA method based on model properties, event handling, and automatic parallelism on multicore architectures. The underlying structure of the code has been completely updated to provide a flexible framework for extending its functionality. StochKit2 runs on Linux/Unix, Mac OS X and Windows. It is freely available under GPL version 3 and can be downloaded from http://sourceforge.net/projects/stochkit/. petzold@engineering.ucsb.edu.

Computer-based route-definition system for peripheral bronchoscopy.

PubMed

Graham, Michael W; Gibbs, Jason D; Higgins, William E

2012-04-01

Multi-detector computed tomography (MDCT) scanners produce high-resolution images of the chest. Given a patient's MDCT scan, a physician can use an image-guided intervention system to first plan and later perform bronchoscopy to diagnostic sites situated deep in the lung periphery. An accurate definition of complete routes through the airway tree leading to the diagnostic sites, however, is vital for avoiding navigation errors during image-guided bronchoscopy. We present a system for the robust definition of complete airway routes suitable for image-guided bronchoscopy. The system incorporates both automatic and semiautomatic MDCT analysis methods for this purpose. Using an intuitive graphical user interface, the user invokes automatic analysis on a patient's MDCT scan to produce a series of preliminary routes. Next, the user visually inspects each route and quickly corrects the observed route defects using the built-in semiautomatic methods. Application of the system to a human study for the planning and guidance of peripheral bronchoscopy demonstrates the efficacy of the system.

Comparing a novel automatic 3D method for LGE-CMR quantification of scar size with established methods.

PubMed

Woie, Leik; Måløy, Frode; Eftestøl, Trygve; Engan, Kjersti; Edvardsen, Thor; Kvaløy, Jan Terje; Ørn, Stein

2014-02-01

Current methods for the estimation of infarct size by late-enhanced cardiac magnetic imaging are based upon 2D analysis that first determines the size of the infarction in each slice, and thereafter adds the infarct sizes from each slice to generate a volume. We present a novel, automatic 3D method that estimates infarct size by a simultaneous analysis of all pixels from all slices. In a population of 54 patients with ischemic scars, the infarct size estimated by the automatic 3D method was compared with four established 2D methods. The new 3D method defined scar as the sum of all pixels with signal intensity (SI) ≥35 % of max SI from the complete myocardium, border zone: SI 35-50 % of max SI and core as SI ≥50 % of max SI. The 3D method yielded smaller infarct size (-2.8 ± 2.3 %) and core size (-3.0 ± 1.7 %) than the 2D method most similar to ours. There was no difference in the size of the border zone (0.2 ± 1.4 %). The 3D method demonstrated stronger correlations between scar size and left ventricular (LV) remodelling parameters (LV ejection fraction: r = -0.71, p < 0.0005, LV end-diastolic index: r = 0.54, p < 0.0005, and LV end-systolic index: r = 0.59, p < 0.0005) compared with conventional 2D methods. Infarct size estimation by our novel 3D automatic method is without the need for manual demarcation of the scar; it is less time-consuming and has a stronger correlation with remodelling parameters compared with existing methods.

Automatic categorization of diverse experimental information in the bioscience literature

PubMed Central

2012-01-01

Background Curation of information from bioscience literature into biological knowledge databases is a crucial way of capturing experimental information in a computable form. During the biocuration process, a critical first step is to identify from all published literature the papers that contain results for a specific data type the curator is interested in annotating. This step normally requires curators to manually examine many papers to ascertain which few contain information of interest and thus, is usually time consuming. We developed an automatic method for identifying papers containing these curation data types among a large pool of published scientific papers based on the machine learning method Support Vector Machine (SVM). This classification system is completely automatic and can be readily applied to diverse experimental data types. It has been in use in production for automatic categorization of 10 different experimental datatypes in the biocuration process at WormBase for the past two years and it is in the process of being adopted in the biocuration process at FlyBase and the Saccharomyces Genome Database (SGD). We anticipate that this method can be readily adopted by various databases in the biocuration community and thereby greatly reducing time spent on an otherwise laborious and demanding task. We also developed a simple, readily automated procedure to utilize training papers of similar data types from different bodies of literature such as C. elegans and D. melanogaster to identify papers with any of these data types for a single database. This approach has great significance because for some data types, especially those of low occurrence, a single corpus often does not have enough training papers to achieve satisfactory performance. Results We successfully tested the method on ten data types from WormBase, fifteen data types from FlyBase and three data types from Mouse Genomics Informatics (MGI). It is being used in the curation work flow at WormBase for automatic association of newly published papers with ten data types including RNAi, antibody, phenotype, gene regulation, mutant allele sequence, gene expression, gene product interaction, overexpression phenotype, gene interaction, and gene structure correction. Conclusions Our methods are applicable to a variety of data types with training set containing several hundreds to a few thousand documents. It is completely automatic and, thus can be readily incorporated to different workflow at different literature-based databases. We believe that the work presented here can contribute greatly to the tremendous task of automating the important yet labor-intensive biocuration effort. PMID:22280404

Automatic categorization of diverse experimental information in the bioscience literature.

PubMed

Fang, Ruihua; Schindelman, Gary; Van Auken, Kimberly; Fernandes, Jolene; Chen, Wen; Wang, Xiaodong; Davis, Paul; Tuli, Mary Ann; Marygold, Steven J; Millburn, Gillian; Matthews, Beverley; Zhang, Haiyan; Brown, Nick; Gelbart, William M; Sternberg, Paul W

2012-01-26

Curation of information from bioscience literature into biological knowledge databases is a crucial way of capturing experimental information in a computable form. During the biocuration process, a critical first step is to identify from all published literature the papers that contain results for a specific data type the curator is interested in annotating. This step normally requires curators to manually examine many papers to ascertain which few contain information of interest and thus, is usually time consuming. We developed an automatic method for identifying papers containing these curation data types among a large pool of published scientific papers based on the machine learning method Support Vector Machine (SVM). This classification system is completely automatic and can be readily applied to diverse experimental data types. It has been in use in production for automatic categorization of 10 different experimental datatypes in the biocuration process at WormBase for the past two years and it is in the process of being adopted in the biocuration process at FlyBase and the Saccharomyces Genome Database (SGD). We anticipate that this method can be readily adopted by various databases in the biocuration community and thereby greatly reducing time spent on an otherwise laborious and demanding task. We also developed a simple, readily automated procedure to utilize training papers of similar data types from different bodies of literature such as C. elegans and D. melanogaster to identify papers with any of these data types for a single database. This approach has great significance because for some data types, especially those of low occurrence, a single corpus often does not have enough training papers to achieve satisfactory performance. We successfully tested the method on ten data types from WormBase, fifteen data types from FlyBase and three data types from Mouse Genomics Informatics (MGI). It is being used in the curation work flow at WormBase for automatic association of newly published papers with ten data types including RNAi, antibody, phenotype, gene regulation, mutant allele sequence, gene expression, gene product interaction, overexpression phenotype, gene interaction, and gene structure correction. Our methods are applicable to a variety of data types with training set containing several hundreds to a few thousand documents. It is completely automatic and, thus can be readily incorporated to different workflow at different literature-based databases. We believe that the work presented here can contribute greatly to the tremendous task of automating the important yet labor-intensive biocuration effort.

[Automation of chemical analysis in enology].

PubMed

Dubernet, M

1978-01-01

Automatic dosages took place a short time ago in oenology laboratories. First researchs about automation of usual manual analysis have been completed by I.N.R.A. Station of Dijon during 1969--1972 years. Then, other researchs were made and in 1974 the first automatic analyser appeared in application laboratories. In all cases continuous flow method was used. First dosages which has been carried out are volatic acidity, residual sugars, total SO2. The rate of work is 30 samples an hour. Then, an original way for free SO2 was suggested. At present, about a dozen of laboratories in France use these dosages. The ethanol dosage automation, very important in oenology, is very difficult to carry out. A new method using a thermometric analyzer is tested. Research about many dosages as tartaric, malic, lactic acids, glucose, fructose, glycérol, have been performed especially by I.N.R.A. Station in Narbonne. But these dosages are not current and at present no laboratory apply them. Now, equipments price and redemption, change of tradionnal dosages for automatical methods and the level of knowledge required for operators are well known. The reproducibility and the accuracy of the continuous flow automatic dosages allow, for enough important laboratories, to make an increasing number of analysis necessary for wine quality control.

70. VIEW OF PARTIALLY COMPLETED FLUME BELOW THE AUTOMATIC SPILL ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

70. VIEW OF PARTIALLY COMPLETED FLUME BELOW THE AUTOMATIC SPILL AT THE RESERVOIR, SHOWING MOUNT RAINIER IN THE DISTANCE, Print No. 192, December 1903 - Electron Hydroelectric Project, Along Puyallup River, Electron, Pierce County, WA

Automatic diagnosis of malaria based on complete circle-ellipse fitting search algorithm.

PubMed

Sheikhhosseini, M; Rabbani, H; Zekri, M; Talebi, A

2013-12-01

Diagnosis of malaria parasitemia from blood smears is a subjective and time-consuming task for pathologists. The automatic diagnostic process will reduce the diagnostic time. Also, it can be worked as a second opinion for pathologists and may be useful in malaria screening. This study presents an automatic method for malaria diagnosis from thin blood smears. According to this fact that malaria life cycle is started by forming a ring around the parasite nucleus, the proposed approach is mainly based on curve fitting to detect parasite ring in the blood smear. The method is composed of six main phases: stain object extraction step, which extracts candidate objects that may be infected by malaria parasites. This phase includes stained pixel extraction step based on intensity and colour, and stained object segmentation by defining stained circle matching. Second step is preprocessing phase which makes use of nonlinear diffusion filtering. The process continues with detection of parasite nucleus from resulted image of previous step according to image intensity. Fourth step introduces a complete search process in which the circle search step identifies the direction and initial points for direct least-square ellipse fitting algorithm. Furthermore in the ellipse searching process, although parasite shape is completed undesired regions with high error value are removed and ellipse parameters are modified. Features are extracted from the parasite candidate region instead of whole candidate object in the fifth step. By employing this special feature extraction way, which is provided by special searching process, the necessity of employing clump splitting methods is removed. Also, defining stained circle matching process in the first step speeds up the whole procedure. Finally, a series of decision rules are applied on the extracted features to decide on the positivity or negativity of malaria parasite presence. The algorithm is applied on 26 digital images which are provided from thin blood smear films. The images are contained 1274 objects which may be infected by parasite or healthy. Applying the automatic identification of malaria on provided database showed a sensitivity of 82.28% and specificity of 98.02%. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Sampling theory and automated simulations for vertical sections, applied to human brain.

PubMed

Cruz-Orive, L M; Gelšvartas, J; Roberts, N

2014-02-01

In recent years, there have been substantial developments in both magnetic resonance imaging techniques and automatic image analysis software. The purpose of this paper is to develop stereological image sampling theory (i.e. unbiased sampling rules) that can be used by image analysts for estimating geometric quantities such as surface area and volume, and to illustrate its implementation. The methods will ideally be applied automatically on segmented, properly sampled 2D images - although convenient manual application is always an option - and they are of wide applicability in many disciplines. In particular, the vertical sections design to estimate surface area is described in detail and applied to estimate the area of the pial surface and of the boundary between cortex and underlying white matter (i.e. subcortical surface area). For completeness, cortical volume and mean cortical thickness are also estimated. The aforementioned surfaces were triangulated in 3D with the aid of FreeSurfer software, which provided accurate surface area measures that served as gold standards. Furthermore, a software was developed to produce digitized trace curves of the triangulated target surfaces automatically from virtual sections. From such traces, a new method (called the 'lambda method') is presented to estimate surface area automatically. In addition, with the new software, intersections could be counted automatically between the relevant surface traces and a cycloid test grid for the classical design. This capability, together with the aforementioned gold standard, enabled us to thoroughly check the performance and the variability of the different estimators by Monte Carlo simulations for studying the human brain. In particular, new methods are offered to split the total error variance into the orientations, sectioning and cycloid components. The latter prediction was hitherto unavailable--one is proposed here and checked by way of simulations on a given set of digitized vertical sections with automatically superimposed cycloid grids of three different sizes. Concrete and detailed recommendations are given to implement the methods. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

A man-made object detection for underwater TV

NASA Astrophysics Data System (ADS)

Cheng, Binbin; Wang, Wenwu; Chen, Yao

2018-03-01

It is a great challenging task to complete an automatic search of objects underwater. Usually the forward looking sonar is used to find the target, and then the initial identification of the target is completed by the side-scan sonar, and finally the confirmation of the target is accomplished by underwater TV. This paper presents an efficient method for automatic extraction of man-made sensitive targets in underwater TV. Firstly, the image of underwater TV is simplified with taking full advantage of the prior knowledge of the target and the background; then template matching technology is used for target detection; finally the target is confirmed by extracting parallel lines on the target contour. The algorithm is formulated for real-time execution on limited-memory commercial-of-the-shelf platforms and is capable of detection objects in underwater TV.

A semi-automatic traffic sign detection, classification, and positioning system

NASA Astrophysics Data System (ADS)

Creusen, I. M.; Hazelhoff, L.; de With, P. H. N.

2012-01-01

The availability of large-scale databases containing street-level panoramic images offers the possibility to perform semi-automatic surveying of real-world objects such as traffic signs. These inventories can be performed significantly more efficiently than using conventional methods. Governmental agencies are interested in these inventories for maintenance and safety reasons. This paper introduces a complete semi-automatic traffic sign inventory system. The system consists of several components. First, a detection algorithm locates the 2D position of the traffic signs in the panoramic images. Second, a classification algorithm is used to identify the traffic sign. Third, the 3D position of the traffic sign is calculated using the GPS position of the photographs. Finally, the results are listed in a table for quick inspection and are also visualized in a web browser.

Automatic Detection and Positioning of Ground Control Points Using TerraSAR-X Multiaspect Acquisitions

NASA Astrophysics Data System (ADS)

Montazeri, Sina; Gisinger, Christoph; Eineder, Michael; Zhu, Xiao xiang

2018-05-01

Geodetic stereo Synthetic Aperture Radar (SAR) is capable of absolute three-dimensional localization of natural Persistent Scatterer (PS)s which allows for Ground Control Point (GCP) generation using only SAR data. The prerequisite for the method to achieve high precision results is the correct detection of common scatterers in SAR images acquired from different viewing geometries. In this contribution, we describe three strategies for automatic detection of identical targets in SAR images of urban areas taken from different orbit tracks. Moreover, a complete work-flow for automatic generation of large number of GCPs using SAR data is presented and its applicability is shown by exploiting TerraSAR-X (TS-X) high resolution spotlight images over the city of Oulu, Finland and a test site in Berlin, Germany.

Automatic face recognition in HDR imaging

NASA Astrophysics Data System (ADS)

Pereira, Manuela; Moreno, Juan-Carlos; Proença, Hugo; Pinheiro, António M. G.

2014-05-01

The gaining popularity of the new High Dynamic Range (HDR) imaging systems is raising new privacy issues caused by the methods used for visualization. HDR images require tone mapping methods for an appropriate visualization on conventional and non-expensive LDR displays. These visualization methods might result in completely different visualization raising several issues on privacy intrusion. In fact, some visualization methods result in a perceptual recognition of the individuals, while others do not even show any identity. Although perceptual recognition might be possible, a natural question that can rise is how computer based recognition will perform using tone mapping generated images? In this paper, a study where automatic face recognition using sparse representation is tested with images that result from common tone mapping operators applied to HDR images. Its ability for the face identity recognition is described. Furthermore, typical LDR images are used for the face recognition training.

Automatic Centerline Extraction of Coverd Roads by Surrounding Objects from High Resolution Satellite Images

NASA Astrophysics Data System (ADS)

Kamangir, H.; Momeni, M.; Satari, M.

2017-09-01

This paper presents an automatic method to extract road centerline networks from high and very high resolution satellite images. The present paper addresses the automated extraction roads covered with multiple natural and artificial objects such as trees, vehicles and either shadows of buildings or trees. In order to have a precise road extraction, this method implements three stages including: classification of images based on maximum likelihood algorithm to categorize images into interested classes, modification process on classified images by connected component and morphological operators to extract pixels of desired objects by removing undesirable pixels of each class, and finally line extraction based on RANSAC algorithm. In order to evaluate performance of the proposed method, the generated results are compared with ground truth road map as a reference. The evaluation performance of the proposed method using representative test images show completeness values ranging between 77% and 93%.

Automatic choroid cells segmentation and counting in fluorescence microscopic image

NASA Astrophysics Data System (ADS)

Fei, Jianjun; Zhu, Weifang; Shi, Fei; Xiang, Dehui; Lin, Xiao; Yang, Lei; Chen, Xinjian

2016-03-01

In this paper, we proposed a method to automatically segment and count the rhesus choroid-retinal vascular endothelial cells (RF/6A) in fluorescence microscopic images which is based on shape classification, bottleneck detection and accelerated Dijkstra algorithm. The proposed method includes four main steps. First, a thresholding filter and morphological operations are applied to reduce the noise. Second, a shape classifier is used to decide whether a connected component is needed to be segmented. In this step, the AdaBoost classifier is applied with a set of shape features. Third, the bottleneck positions are found based on the contours of the connected components. Finally, the cells segmentation and counting are completed based on the accelerated Dijkstra algorithm with the gradient information between the bottleneck positions. The results show the feasibility and efficiency of the proposed method.

Haptic exploratory behavior during object discrimination: a novel automatic annotation method.

PubMed

Jansen, Sander E M; Bergmann Tiest, Wouter M; Kappers, Astrid M L

2015-01-01

In order to acquire information concerning the geometry and material of handheld objects, people tend to execute stereotypical hand movement patterns called haptic Exploratory Procedures (EPs). Manual annotation of haptic exploration trials with these EPs is a laborious task that is affected by subjectivity, attentional lapses, and viewing angle limitations. In this paper we propose an automatic EP annotation method based on position and orientation data from motion tracking sensors placed on both hands and inside a stimulus. A set of kinematic variables is computed from these data and compared to sets of predefined criteria for each of four EPs. Whenever all criteria for a specific EP are met, it is assumed that that particular hand movement pattern was performed. This method is applied to data from an experiment where blindfolded participants haptically discriminated between objects differing in hardness, roughness, volume, and weight. In order to validate the method, its output is compared to manual annotation based on video recordings of the same trials. Although mean pairwise agreement is less between human-automatic pairs than between human-human pairs (55.7% vs 74.5%), the proposed method performs much better than random annotation (2.4%). Furthermore, each EP is linked to a specific object property for which it is optimal (e.g., Lateral Motion for roughness). We found that the percentage of trials where the expected EP was found does not differ between manual and automatic annotation. For now, this method cannot yet completely replace a manual annotation procedure. However, it could be used as a starting point that can be supplemented by manual annotation.

Direct volume estimation without segmentation

NASA Astrophysics Data System (ADS)

Zhen, X.; Wang, Z.; Islam, A.; Bhaduri, M.; Chan, I.; Li, S.

2015-03-01

Volume estimation plays an important role in clinical diagnosis. For example, cardiac ventricular volumes including left ventricle (LV) and right ventricle (RV) are important clinical indicators of cardiac functions. Accurate and automatic estimation of the ventricular volumes is essential to the assessment of cardiac functions and diagnosis of heart diseases. Conventional methods are dependent on an intermediate segmentation step which is obtained either manually or automatically. However, manual segmentation is extremely time-consuming, subjective and highly non-reproducible; automatic segmentation is still challenging, computationally expensive, and completely unsolved for the RV. Towards accurate and efficient direct volume estimation, our group has been researching on learning based methods without segmentation by leveraging state-of-the-art machine learning techniques. Our direct estimation methods remove the accessional step of segmentation and can naturally deal with various volume estimation tasks. Moreover, they are extremely flexible to be used for volume estimation of either joint bi-ventricles (LV and RV) or individual LV/RV. We comparatively study the performance of direct methods on cardiac ventricular volume estimation by comparing with segmentation based methods. Experimental results show that direct estimation methods provide more accurate estimation of cardiac ventricular volumes than segmentation based methods. This indicates that direct estimation methods not only provide a convenient and mature clinical tool for cardiac volume estimation but also enables diagnosis of cardiac diseases to be conducted in a more efficient and reliable way.

A green method of diaphragm spring's anti-rusting with high quality and efficiency

NASA Astrophysics Data System (ADS)

Huang, Xinming; Hua, Wenlin

2017-10-01

This paper introduces a green method of diaphragm spring's anti-rusting, which is of high quality, high efficiency and low consumption. It transforms the phosphating way of anti-rusting to physical anti-rusting that directly coat anti-rusting oil on the surface of the spring, and transforms the manual-oiling or oil-immersion to fully-automatically ultrasonic oiling. Hence, this method will completely change the way of diaphgragm spring's anti-rusting.

INFORMATION STORAGE AND RETRIEVAL, REPORTS ON EVALUATION, CLUSTERING, AND FEEDBACK.

ERIC Educational Resources Information Center

SALTON, GERALD

THE TWELFTH IN A SERIES COVERING RESEARCH IN AUTOMATIC STORAGE AND RETRIEVAL, THIS REPORT IS DIVIDED INTO THREE PARTS TITLED EVALUATION, CLUSTER SEARCHING, AND USER FEEDBACK METHODS, RESPECTIVELY. THE FIRST PART, EVALUATION, CONTAINS A COMPLETE SUMMARY OF THE RETRIEVAL RESULTS DERIVED FROM SOME SIXTY DIFFERENT TEXT ANALYSIS EXPERIMENTS. IN EACH…

Consistent model driven architecture

NASA Astrophysics Data System (ADS)

Niepostyn, Stanisław J.

2015-09-01

The goal of the MDA is to produce software systems from abstract models in a way where human interaction is restricted to a minimum. These abstract models are based on the UML language. However, the semantics of UML models is defined in a natural language. Subsequently the verification of consistency of these diagrams is needed in order to identify errors in requirements at the early stage of the development process. The verification of consistency is difficult due to a semi-formal nature of UML diagrams. We propose automatic verification of consistency of the series of UML diagrams originating from abstract models implemented with our consistency rules. This Consistent Model Driven Architecture approach enables us to generate automatically complete workflow applications from consistent and complete models developed from abstract models (e.g. Business Context Diagram). Therefore, our method can be used to check practicability (feasibility) of software architecture models.

Algorithm based on regional separation for automatic grain boundary extraction using improved mean shift method

NASA Astrophysics Data System (ADS)

Zhenying, Xu; Jiandong, Zhu; Qi, Zhang; Yamba, Philip

2018-06-01

Metallographic microscopy shows that the vast majority of metal materials are composed of many small grains; the grain size of a metal is important for determining the tensile strength, toughness, plasticity, and other mechanical properties. In order to quantitatively evaluate grain size in metals, grain boundaries must be identified in metallographic images. Based on the phenomenon of grain boundary blurring or disconnection in metallographic images, this study develops an algorithm based on regional separation for automatically extracting grain boundaries by an improved mean shift method. Experimental observation shows that the grain boundaries obtained by the proposed algorithm are highly complete and accurate. This research has practical value because the proposed algorithm is suitable for grain boundary extraction from most metallographic images.

Reconstruction of three-dimensional grain structure in polycrystalline iron via an interactive segmentation method

NASA Astrophysics Data System (ADS)

Feng, Min-nan; Wang, Yu-cong; Wang, Hao; Liu, Guo-quan; Xue, Wei-hua

2017-03-01

Using a total of 297 segmented sections, we reconstructed the three-dimensional (3D) structure of pure iron and obtained the largest dataset of 16254 3D complete grains reported to date. The mean values of equivalent sphere radius and face number of pure iron were observed to be consistent with those of Monte Carlo simulated grains, phase-field simulated grains, Ti-alloy grains, and Ni-based super alloy grains. In this work, by finding a balance between automatic methods and manual refinement, we developed an interactive segmentation method to segment serial sections accurately in the reconstruction of the 3D microstructure; this approach can save time as well as substantially eliminate errors. The segmentation process comprises four operations: image preprocessing, breakpoint detection based on mathematical morphology analysis, optimized automatic connection of the breakpoints, and manual refinement by artificial evaluation.

Automatic segmentation of mandible in panoramic x-ray.

PubMed

Abdi, Amir Hossein; Kasaei, Shohreh; Mehdizadeh, Mojdeh

2015-10-01

As the panoramic x-ray is the most common extraoral radiography in dentistry, segmentation of its anatomical structures facilitates diagnosis and registration of dental records. This study presents a fast and accurate method for automatic segmentation of mandible in panoramic x-rays. In the proposed four-step algorithm, a superior border is extracted through horizontal integral projections. A modified Canny edge detector accompanied by morphological operators extracts the inferior border of the mandible body. The exterior borders of ramuses are extracted through a contour tracing method based on the average model of mandible. The best-matched template is fetched from the atlas of mandibles to complete the contour of left and right processes. The algorithm was tested on a set of 95 panoramic x-rays. Evaluating the results against manual segmentations of three expert dentists showed that the method is robust. It achieved an average performance of [Formula: see text] in Dice similarity, specificity, and sensitivity.

Is STAPLE algorithm confident to assess segmentation methods in PET imaging?

NASA Astrophysics Data System (ADS)

Dewalle-Vignion, Anne-Sophie; Betrouni, Nacim; Baillet, Clio; Vermandel, Maximilien

2015-12-01

Accurate tumor segmentation in [18F]-fluorodeoxyglucose positron emission tomography is crucial for tumor response assessment and target volume definition in radiation therapy. Evaluation of segmentation methods from clinical data without ground truth is usually based on physicians’ manual delineations. In this context, the simultaneous truth and performance level estimation (STAPLE) algorithm could be useful to manage the multi-observers variability. In this paper, we evaluated how this algorithm could accurately estimate the ground truth in PET imaging. Complete evaluation study using different criteria was performed on simulated data. The STAPLE algorithm was applied to manual and automatic segmentation results. A specific configuration of the implementation provided by the Computational Radiology Laboratory was used. Consensus obtained by the STAPLE algorithm from manual delineations appeared to be more accurate than manual delineations themselves (80% of overlap). An improvement of the accuracy was also observed when applying the STAPLE algorithm to automatic segmentations results. The STAPLE algorithm, with the configuration used in this paper, is more appropriate than manual delineations alone or automatic segmentations results alone to estimate the ground truth in PET imaging. Therefore, it might be preferred to assess the accuracy of tumor segmentation methods in PET imaging.

Is STAPLE algorithm confident to assess segmentation methods in PET imaging?

PubMed

Dewalle-Vignion, Anne-Sophie; Betrouni, Nacim; Baillet, Clio; Vermandel, Maximilien

2015-12-21

Accurate tumor segmentation in [18F]-fluorodeoxyglucose positron emission tomography is crucial for tumor response assessment and target volume definition in radiation therapy. Evaluation of segmentation methods from clinical data without ground truth is usually based on physicians' manual delineations. In this context, the simultaneous truth and performance level estimation (STAPLE) algorithm could be useful to manage the multi-observers variability. In this paper, we evaluated how this algorithm could accurately estimate the ground truth in PET imaging. Complete evaluation study using different criteria was performed on simulated data. The STAPLE algorithm was applied to manual and automatic segmentation results. A specific configuration of the implementation provided by the Computational Radiology Laboratory was used. Consensus obtained by the STAPLE algorithm from manual delineations appeared to be more accurate than manual delineations themselves (80% of overlap). An improvement of the accuracy was also observed when applying the STAPLE algorithm to automatic segmentations results. The STAPLE algorithm, with the configuration used in this paper, is more appropriate than manual delineations alone or automatic segmentations results alone to estimate the ground truth in PET imaging. Therefore, it might be preferred to assess the accuracy of tumor segmentation methods in PET imaging.

A new user-assisted segmentation and tracking technique for an object-based video editing system

NASA Astrophysics Data System (ADS)

Yu, Hong Y.; Hong, Sung-Hoon; Lee, Mike M.; Choi, Jae-Gark

2004-03-01

This paper presents a semi-automatic segmentation method which can be used to generate video object plane (VOP) for object based coding scheme and multimedia authoring environment. Semi-automatic segmentation can be considered as a user-assisted segmentation technique. A user can initially mark objects of interest around the object boundaries and then the user-guided and selected objects are continuously separated from the unselected areas through time evolution in the image sequences. The proposed segmentation method consists of two processing steps: partially manual intra-frame segmentation and fully automatic inter-frame segmentation. The intra-frame segmentation incorporates user-assistance to define the meaningful complete visual object of interest to be segmentation and decides precise object boundary. The inter-frame segmentation involves boundary and region tracking to obtain temporal coherence of moving object based on the object boundary information of previous frame. The proposed method shows stable efficient results that could be suitable for many digital video applications such as multimedia contents authoring, content based coding and indexing. Based on these results, we have developed objects based video editing system with several convenient editing functions.

Automatic rectum limit detection by anatomical markers correlation.

PubMed

Namías, R; D'Amato, J P; del Fresno, M; Vénere, M

2014-06-01

Several diseases take place at the end of the digestive system. Many of them can be diagnosed by means of different medical imaging modalities together with computer aided detection (CAD) systems. These CAD systems mainly focus on the complete segmentation of the digestive tube. However, the detection of limits between different sections could provide important information to these systems. In this paper we present an automatic method for detecting the rectum and sigmoid colon limit using a novel global curvature analysis over the centerline of the segmented digestive tube in different imaging modalities. The results are compared with the gold standard rectum upper limit through a validation scheme comprising two different anatomical markers: the third sacral vertebra and the average rectum length. Experimental results in both magnetic resonance imaging (MRI) and computed tomography colonography (CTC) acquisitions show the efficacy of the proposed strategy in automatic detection of rectum limits. The method is intended for application to the rectum segmentation in MRI for geometrical modeling and as contextual information source in virtual colonoscopies and CAD systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Automatic data-processing equipment of moon mark of nail for verifying some experiential theory of Traditional Chinese Medicine.

PubMed

Niu, Renjie; Fu, Chenyu; Xu, Zhiyong; Huang, Jianyuan

2016-04-29

Doctors who practice Traditional Chinese Medicine (TCM) diagnose using four methods - inspection, auscultation and olfaction, interrogation, and pulse feeling/palpation. The shape and shape changes of the moon marks on the nails are an important indication when judging the patient's health. There are a series of classical and experimental theories about moon marks in TCM, which does not have support from statistical data. To verify some experiential theories on moon mark in TCM by automatic data-processing equipment. This paper proposes the equipment that utilizes image processing technology to collect moon mark data of different target groups conveniently and quickly, building a database that combines this information with that gathered from the health and mental status questionnaire in each test. This equipment has a simple design, a low cost, and an optimized algorithm. The practice has been proven to quickly complete automatic acquisition and preservation of key data about moon marks. In the future, some conclusions will likely be obtained from these data; some changes of moon marks related to a special pathological change will be established with statistical methods.

Biosignal Analysis to Assess Mental Stress in Automatic Driving of Trucks: Palmar Perspiration and Masseter Electromyography

PubMed Central

Zheng, Rencheng; Yamabe, Shigeyuki; Nakano, Kimihiko; Suda, Yoshihiro

2015-01-01

Nowadays insight into human-machine interaction is a critical topic with the large-scale development of intelligent vehicles. Biosignal analysis can provide a deeper understanding of driver behaviors that may indicate rationally practical use of the automatic technology. Therefore, this study concentrates on biosignal analysis to quantitatively evaluate mental stress of drivers during automatic driving of trucks, with vehicles set at a closed gap distance apart to reduce air resistance to save energy consumption. By application of two wearable sensor systems, a continuous measurement was realized for palmar perspiration and masseter electromyography, and a biosignal processing method was proposed to assess mental stress levels. In a driving simulator experiment, ten participants completed automatic driving with 4, 8, and 12 m gap distances from the preceding vehicle, and manual driving with about 25 m gap distance as a reference. It was found that mental stress significantly increased when the gap distances decreased, and an abrupt increase in mental stress of drivers was also observed accompanying a sudden change of the gap distance during automatic driving, which corresponded to significantly higher ride discomfort according to subjective reports. PMID:25738768

Self-recalibration of a robot-assisted structured-light-based measurement system.

PubMed

Xu, Jing; Chen, Rui; Liu, Shuntao; Guan, Yong

2017-11-10

The structured-light-based measurement method is widely employed in numerous fields. However, for industrial inspection, to achieve complete scanning of a work piece and overcome occlusion, the measurement system needs to be moved to different viewpoints. Moreover, frequent reconfiguration of the measurement system may be needed based on the size of the measured object, making the self-recalibration of extrinsic parameters indispensable. To this end, this paper proposes an automatic self-recalibration and reconstruction method, wherein a robot arm is employed to move the measurement system for complete scanning; the self-recalibration is achieved using fundamental matrix calculations and point cloud registration without the need for an accurate calibration gauge. Experimental results demonstrate the feasibility and accuracy of our method.

Automatic choroid cells segmentation and counting based on approximate convexity and concavity of chain code in fluorescence microscopic image

NASA Astrophysics Data System (ADS)

Lu, Weihua; Chen, Xinjian; Zhu, Weifang; Yang, Lei; Cao, Zhaoyuan; Chen, Haoyu

2015-03-01

In this paper, we proposed a method based on the Freeman chain code to segment and count rhesus choroid-retinal vascular endothelial cells (RF/6A) automatically for fluorescence microscopy images. The proposed method consists of four main steps. First, a threshold filter and morphological transform were applied to reduce the noise. Second, the boundary information was used to generate the Freeman chain codes. Third, the concave points were found based on the relationship between the difference of the chain code and the curvature. Finally, cells segmentation and counting were completed based on the characteristics of the number of the concave points, the area and shape of the cells. The proposed method was tested on 100 fluorescence microscopic cell images, and the average true positive rate (TPR) is 98.13% and the average false positive rate (FPR) is 4.47%, respectively. The preliminary results showed the feasibility and efficiency of the proposed method.

ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features.

PubMed

Mognon, Andrea; Jovicich, Jorge; Bruzzone, Lorenzo; Buiatti, Marco

2011-02-01

A successful method for removing artifacts from electroencephalogram (EEG) recordings is Independent Component Analysis (ICA), but its implementation remains largely user-dependent. Here, we propose a completely automatic algorithm (ADJUST) that identifies artifacted independent components by combining stereotyped artifact-specific spatial and temporal features. Features were optimized to capture blinks, eye movements, and generic discontinuities on a feature selection dataset. Validation on a totally different EEG dataset shows that (1) ADJUST's classification of independent components largely matches a manual one by experts (agreement on 95.2% of the data variance), and (2) Removal of the artifacted components detected by ADJUST leads to neat reconstruction of visual and auditory event-related potentials from heavily artifacted data. These results demonstrate that ADJUST provides a fast, efficient, and automatic way to use ICA for artifact removal. Copyright © 2010 Society for Psychophysiological Research.

Pse-Analysis: a python package for DNA/RNA and protein/ peptide sequence analysis based on pseudo components and kernel methods.

PubMed

Liu, Bin; Wu, Hao; Zhang, Deyuan; Wang, Xiaolong; Chou, Kuo-Chen

2017-02-21

To expedite the pace in conducting genome/proteome analysis, we have developed a Python package called Pse-Analysis. The powerful package can automatically complete the following five procedures: (1) sample feature extraction, (2) optimal parameter selection, (3) model training, (4) cross validation, and (5) evaluating prediction quality. All the work a user needs to do is to input a benchmark dataset along with the query biological sequences concerned. Based on the benchmark dataset, Pse-Analysis will automatically construct an ideal predictor, followed by yielding the predicted results for the submitted query samples. All the aforementioned tedious jobs can be automatically done by the computer. Moreover, the multiprocessing technique was adopted to enhance computational speed by about 6 folds. The Pse-Analysis Python package is freely accessible to the public at http://bioinformatics.hitsz.edu.cn/Pse-Analysis/, and can be directly run on Windows, Linux, and Unix.

Automatic map generalisation from research to production

NASA Astrophysics Data System (ADS)

Nyberg, Rose; Johansson, Mikael; Zhang, Yang

2018-05-01

The manual work of map generalisation is known to be a complex and time consuming task. With the development of technology and societies, the demands for more flexible map products with higher quality are growing. The Swedish mapping, cadastral and land registration authority Lantmäteriet has manual production lines for databases in five different scales, 1 : 10 000 (SE10), 1 : 50 000 (SE50), 1 : 100 000 (SE100), 1 : 250 000 (SE250) and 1 : 1 million (SE1M). To streamline this work, Lantmäteriet started a project to automatically generalise geographic information. Planned timespan for the project is 2015-2022. Below the project background together with the methods for the automatic generalisation are described. The paper is completed with a description of results and conclusions.

Evaluation of Model Recognition for Grammar-Based Automatic 3d Building Model Reconstruction

NASA Astrophysics Data System (ADS)

Yu, Qian; Helmholz, Petra; Belton, David

2016-06-01

In recent years, 3D city models are in high demand by many public and private organisations, and the steadily growing capacity in both quality and quantity are increasing demand. The quality evaluation of these 3D models is a relevant issue both from the scientific and practical points of view. In this paper, we present a method for the quality evaluation of 3D building models which are reconstructed automatically from terrestrial laser scanning (TLS) data based on an attributed building grammar. The entire evaluation process has been performed in all the three dimensions in terms of completeness and correctness of the reconstruction. Six quality measures are introduced to apply on four datasets of reconstructed building models in order to describe the quality of the automatic reconstruction, and also are assessed on their validity from the evaluation point of view.

Accurate and Fully Automatic Hippocampus Segmentation Using Subject-Specific 3D Optimal Local Maps Into a Hybrid Active Contour Model

PubMed Central

Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos

2014-01-01

Assessing the structural integrity of the hippocampus (HC) is an essential step toward prevention, diagnosis, and follow-up of various brain disorders due to the implication of the structural changes of the HC in those disorders. In this respect, the development of automatic segmentation methods that can accurately, reliably, and reproducibly segment the HC has attracted considerable attention over the past decades. This paper presents an innovative 3-D fully automatic method to be used on top of the multiatlas concept for the HC segmentation. The method is based on a subject-specific set of 3-D optimal local maps (OLMs) that locally control the influence of each energy term of a hybrid active contour model (ACM). The complete set of the OLMs for a set of training images is defined simultaneously via an optimization scheme. At the same time, the optimal ACM parameters are also calculated. Therefore, heuristic parameter fine-tuning is not required. Training OLMs are subsequently combined, by applying an extended multiatlas concept, to produce the OLMs that are anatomically more suitable to the test image. The proposed algorithm was tested on three different and publicly available data sets. Its accuracy was compared with that of state-of-the-art methods demonstrating the efficacy and robustness of the proposed method. PMID:27170866

Measuring automatic retrieval: a comparison of implicit memory, process dissociation, and speeded response procedures.

PubMed

Horton, Keith D; Wilson, Daryl E; Vonk, Jennifer; Kirby, Sarah L; Nielsen, Tina

2005-07-01

Using the stem completion task, we compared estimates of automatic retrieval from an implicit memory task, the process dissociation procedure, and the speeded response procedure. Two standard manipulations were employed. In Experiment 1, a depth of processing effect was found on automatic retrieval using the speeded response procedure although this effect was substantially reduced in Experiment 2 when lexical processing was required of all words. In Experiment 3, the speeded response procedure showed an advantage of full versus divided attention at study on automatic retrieval. An implicit condition showed parallel effects in each study, suggesting that implicit stem completion may normally provide a good estimate of automatic retrieval. Also, we replicated earlier findings from the process dissociation procedure, but estimates of automatic retrieval from this procedure were consistently lower than those from the speeded response procedure, except when conscious retrieval was relatively low. We discuss several factors that may contribute to the conflicting outcomes, including the evidence for theoretical assumptions and criterial task differences between implicit and explicit tests.

Automatic Method for Building Indoor Boundary Models from Dense Point Clouds Collected by Laser Scanners

PubMed Central

Valero, Enrique; Adán, Antonio; Cerrada, Carlos

2012-01-01

In this paper we present a method that automatically yields Boundary Representation Models (B-rep) for indoors after processing dense point clouds collected by laser scanners from key locations through an existing facility. Our objective is particularly focused on providing single models which contain the shape, location and relationship of primitive structural elements of inhabited scenarios such as walls, ceilings and floors. We propose a discretization of the space in order to accurately segment the 3D data and generate complete B-rep models of indoors in which faces, edges and vertices are coherently connected. The approach has been tested in real scenarios with data coming from laser scanners yielding promising results. We have deeply evaluated the results by analyzing how reliably these elements can be detected and how accurately they are modeled. PMID:23443369

eulerAPE: Drawing Area-Proportional 3-Venn Diagrams Using Ellipses

PubMed Central

Micallef, Luana; Rodgers, Peter

2014-01-01

Venn diagrams with three curves are used extensively in various medical and scientific disciplines to visualize relationships between data sets and facilitate data analysis. The area of the regions formed by the overlapping curves is often directly proportional to the cardinality of the depicted set relation or any other related quantitative data. Drawing these diagrams manually is difficult and current automatic drawing methods do not always produce appropriate diagrams. Most methods depict the data sets as circles, as they perceptually pop out as complete distinct objects due to their smoothness and regularity. However, circles cannot draw accurate diagrams for most 3-set data and so the generated diagrams often have misleading region areas. Other methods use polygons to draw accurate diagrams. However, polygons are non-smooth and non-symmetric, so the curves are not easily distinguishable and the diagrams are difficult to comprehend. Ellipses are more flexible than circles and are similarly smooth, but none of the current automatic drawing methods use ellipses. We present eulerAPE as the first method and software that uses ellipses for automatically drawing accurate area-proportional Venn diagrams for 3-set data. We describe the drawing method adopted by eulerAPE and we discuss our evaluation of the effectiveness of eulerAPE and ellipses for drawing random 3-set data. We compare eulerAPE and various other methods that are currently available and we discuss differences between their generated diagrams in terms of accuracy and ease of understanding for real world data. PMID:25032825

eulerAPE: drawing area-proportional 3-Venn diagrams using ellipses.

PubMed

Micallef, Luana; Rodgers, Peter

2014-01-01

Venn diagrams with three curves are used extensively in various medical and scientific disciplines to visualize relationships between data sets and facilitate data analysis. The area of the regions formed by the overlapping curves is often directly proportional to the cardinality of the depicted set relation or any other related quantitative data. Drawing these diagrams manually is difficult and current automatic drawing methods do not always produce appropriate diagrams. Most methods depict the data sets as circles, as they perceptually pop out as complete distinct objects due to their smoothness and regularity. However, circles cannot draw accurate diagrams for most 3-set data and so the generated diagrams often have misleading region areas. Other methods use polygons to draw accurate diagrams. However, polygons are non-smooth and non-symmetric, so the curves are not easily distinguishable and the diagrams are difficult to comprehend. Ellipses are more flexible than circles and are similarly smooth, but none of the current automatic drawing methods use ellipses. We present eulerAPE as the first method and software that uses ellipses for automatically drawing accurate area-proportional Venn diagrams for 3-set data. We describe the drawing method adopted by eulerAPE and we discuss our evaluation of the effectiveness of eulerAPE and ellipses for drawing random 3-set data. We compare eulerAPE and various other methods that are currently available and we discuss differences between their generated diagrams in terms of accuracy and ease of understanding for real world data.

Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images.

PubMed

Pereira, Sergio; Pinto, Adriano; Alves, Victor; Silva, Carlos A

2016-05-01

Among brain tumors, gliomas are the most common and aggressive, leading to a very short life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the quality of life of oncological patients. Magnetic resonance imaging (MRI) is a widely used imaging technique to assess these tumors, but the large amount of data produced by MRI prevents manual segmentation in a reasonable time, limiting the use of precise quantitative measurements in the clinical practice. So, automatic and reliable segmentation methods are required; however, the large spatial and structural variability among brain tumors make automatic segmentation a challenging problem. In this paper, we propose an automatic segmentation method based on Convolutional Neural Networks (CNN), exploring small 3 ×3 kernels. The use of small kernels allows designing a deeper architecture, besides having a positive effect against overfitting, given the fewer number of weights in the network. We also investigated the use of intensity normalization as a pre-processing step, which though not common in CNN-based segmentation methods, proved together with data augmentation to be very effective for brain tumor segmentation in MRI images. Our proposal was validated in the Brain Tumor Segmentation Challenge 2013 database (BRATS 2013), obtaining simultaneously the first position for the complete, core, and enhancing regions in Dice Similarity Coefficient metric (0.88, 0.83, 0.77) for the Challenge data set. Also, it obtained the overall first position by the online evaluation platform. We also participated in the on-site BRATS 2015 Challenge using the same model, obtaining the second place, with Dice Similarity Coefficient metric of 0.78, 0.65, and 0.75 for the complete, core, and enhancing regions, respectively.

An automatic, stagnation point based algorithm for the delineation of Wellhead Protection Areas

NASA Astrophysics Data System (ADS)

Tosco, Tiziana; Sethi, Rajandrea; di Molfetta, Antonio

2008-07-01

Time-related capture areas are usually delineated using the backward particle tracking method, releasing circles of equally spaced particles around each well. In this way, an accurate delineation often requires both a very high number of particles and a manual capture zone encirclement. The aim of this work was to propose an Automatic Protection Area (APA) delineation algorithm, which can be coupled with any model of flow and particle tracking. The computational time is here reduced, thanks to the use of a limited number of nonequally spaced particles. The particle starting positions are determined coupling forward particle tracking from the stagnation point, and backward particle tracking from the pumping well. The pathlines are postprocessed for a completely automatic delineation of closed perimeters of time-related capture zones. The APA algorithm was tested for a two-dimensional geometry, in homogeneous and nonhomogeneous aquifers, steady state flow conditions, single and multiple wells. Results show that the APA algorithm is robust and able to automatically and accurately reconstruct protection areas with a very small number of particles, also in complex scenarios.

Automated MeSH indexing of the World-Wide Web.

PubMed Central

Fowler, J.; Kouramajian, V.; Maram, S.; Devadhar, V.

1995-01-01

To facilitate networked discovery and information retrieval in the biomedical domain, we have designed a system for automatic assignment of Medical Subject Headings to documents retrieved from the World-Wide Web. Our prototype implementations show significant promise. We describe our methods and discuss the further development of a completely automated indexing tool called the "Web-MeSH Medibot." PMID:8563421

Low-derivative operators of the Standard Model effective field theory via Hilbert series methods

NASA Astrophysics Data System (ADS)

Lehman, Landon; Martin, Adam

2016-02-01

In this work, we explore an extension of Hilbert series techniques to count operators that include derivatives. For sufficiently low-derivative operators, we conjecture an algorithm that gives the number of invariant operators, properly accounting for redundancies due to the equations of motion and integration by parts. Specifically, the conjectured technique can be applied whenever there is only one Lorentz invariant for a given partitioning of derivatives among the fields. At higher numbers of derivatives, equation of motion redundancies can be removed, but the increased number of Lorentz contractions spoils the subtraction of integration by parts redundancies. While restricted, this technique is sufficient to automatically recreate the complete set of invariant operators of the Standard Model effective field theory for dimensions 6 and 7 (for arbitrary numbers of flavors). At dimension 8, the algorithm does not automatically generate the complete operator set; however, it suffices for all but five classes of operators. For these remaining classes, there is a well defined procedure to manually determine the number of invariants. Assuming our method is correct, we derive a set of 535 dimension-8 N f = 1 operators.

[Study on the appropriate parameters of automatic full crown tooth preparation for dental tooth preparation robot].

PubMed

Yuan, F S; Wang, Y; Zhang, Y P; Sun, Y C; Wang, D X; Lyu, P J

2017-05-09

Objective: To further study the most suitable parameters for automatic full crown preparation using oral clinical micro robot. Its purpose is to improve the quality of automated tooth preparing for the system and to lay the foundation for clinical application. Methods: Twenty selected artificial resin teeth were used as sample teeth. The micro robot automatic tooth preparation system was used in dental clinic to control the picosecond laser beam to complete two dimensional cutting on the resin tooth sample according to the motion planning path. Using the laser scanning measuring microscope, each layer of cutting depth values was obtained and the average value was calculated. The monolayer cutting depth was determined. The three-dimensional (3D) data of the target resin teeth was obtained using internal scanner, and the CAD data of full-crown tooth preparation was designed by CAD self-develged software. According to the depth of the single layer, 11 complete resin teeth in phantom head were automatically prepared by the robot controlling the laser focused spot in accordance with the layer-cutting way. And the accuracy of resin tooth preparation was evaluated with the software. Using the same method, monolayer cutting depth parameter for cutting dental hard tissue was obtained. Then 15 extracted mandibular and maxillary first molars went through automatic full crown tooth preparation. And the 3D data of tooth preparations were obtained with intra oral scanner. The software was used to evaluate the accuracy of tooth preparation. Results: The results indicated that the single cutting depth of cutting resin teeth and in vitro teeth by picosecond laser were (60.0±2.6) and (45.0±3.6) μm, respectively. Using the tooth preparation robot, 11 artificial resin teeth and 15 complete natural teeth were automatically prepared, and the average time were (13.0±0.7), (17.0±1.8) min respectively. Through software evaluation, the average preparation depth of the occlusal surface of 11 resin teeth was approximately (2.089±0.026) mm, the error was about (0.089±0.026) mm; the average convergence angle was about 6.56°±0.30°, the error was about 0.56°±0.30°. Compared with the target preparation shape, the average shape error of the 11 resin tooth preparations was about 0.02-0.11 mm. And the average preparation depth of the occlusal surface of 15 natural teeth was approximately (2.097±0.022) mm, the error was about (0.097±0.022) mm; the average convergence angle was about 6.98°±0.35°, the error was about 0.98°±0.35°. Compared with the target preparation shape, the average shape error of the 15 natural tooth preparations was about 0.05-0.17 mm. Conclusions: The experimental results indicate that the automatic tooth preparation for resin teeth and the teeth were completed according to the specific parameters of the single cutting depth by the micro robot controlling picosecond laser respectively, its preparation accuracy met the clinical needs. And the suitability of the parameter was confirmed.

Automatic Synthesis of Panoramic Radiographs from Dental Cone Beam Computed Tomography Data.

PubMed

Luo, Ting; Shi, Changrong; Zhao, Xing; Zhao, Yunsong; Xu, Jinqiu

2016-01-01

In this paper, we propose an automatic method of synthesizing panoramic radiographs from dental cone beam computed tomography (CBCT) data for directly observing the whole dentition without the superimposition of other structures. This method consists of three major steps. First, the dental arch curve is generated from the maximum intensity projection (MIP) of 3D CBCT data. Then, based on this curve, the long axial curves of the upper and lower teeth are extracted to create a 3D panoramic curved surface describing the whole dentition. Finally, the panoramic radiograph is synthesized by developing this 3D surface. Both open-bite shaped and closed-bite shaped dental CBCT datasets were applied in this study, and the resulting images were analyzed to evaluate the effectiveness of this method. With the proposed method, a single-slice panoramic radiograph can clearly and completely show the whole dentition without the blur and superimposition of other dental structures. Moreover, thickened panoramic radiographs can also be synthesized with increased slice thickness to show more features, such as the mandibular nerve canal. One feature of the proposed method is that it is automatically performed without human intervention. Another feature of the proposed method is that it requires thinner panoramic radiographs to show the whole dentition than those produced by other existing methods, which contributes to the clarity of the anatomical structures, including the enamel, dentine and pulp. In addition, this method can rapidly process common dental CBCT data. The speed and image quality of this method make it an attractive option for observing the whole dentition in a clinical setting.

Pulmonary lobar volumetry using novel volumetric computer-aided diagnosis and computed tomography

PubMed Central

Iwano, Shingo; Kitano, Mariko; Matsuo, Keiji; Kawakami, Kenichi; Koike, Wataru; Kishimoto, Mariko; Inoue, Tsutomu; Li, Yuanzhong; Naganawa, Shinji

2013-01-01

OBJECTIVES To compare the accuracy of pulmonary lobar volumetry using the conventional number of segments method and novel volumetric computer-aided diagnosis using 3D computed tomography images. METHODS We acquired 50 consecutive preoperative 3D computed tomography examinations for lung tumours reconstructed at 1-mm slice thicknesses. We calculated the lobar volume and the emphysematous lobar volume < −950 HU of each lobe using (i) the slice-by-slice method (reference standard), (ii) number of segments method, and (iii) semi-automatic and (iv) automatic computer-aided diagnosis. We determined Pearson correlation coefficients between the reference standard and the three other methods for lobar volumes and emphysematous lobar volumes. We also compared the relative errors among the three measurement methods. RESULTS Both semi-automatic and automatic computer-aided diagnosis results were more strongly correlated with the reference standard than the number of segments method. The correlation coefficients for automatic computer-aided diagnosis were slightly lower than those for semi-automatic computer-aided diagnosis because there was one outlier among 50 cases (2%) in the right upper lobe and two outliers among 50 cases (4%) in the other lobes. The number of segments method relative error was significantly greater than those for semi-automatic and automatic computer-aided diagnosis (P < 0.001). The computational time for automatic computer-aided diagnosis was 1/2 to 2/3 than that of semi-automatic computer-aided diagnosis. CONCLUSIONS A novel lobar volumetry computer-aided diagnosis system could more precisely measure lobar volumes than the conventional number of segments method. Because semi-automatic computer-aided diagnosis and automatic computer-aided diagnosis were complementary, in clinical use, it would be more practical to first measure volumes by automatic computer-aided diagnosis, and then use semi-automatic measurements if automatic computer-aided diagnosis failed. PMID:23526418

Space infrared telescope pointing control system. Automated star pattern recognition

NASA Technical Reports Server (NTRS)

Powell, J. D.; Vanbezooijen, R. W. H.

1985-01-01

The Space Infrared Telescope Facility (SIRTF) is a free flying spacecraft carrying a 1 meter class cryogenically cooled infrared telescope nearly three oders of magnitude most sensitive than the current generation of infrared telescopes. Three automatic target acquisition methods will be presented that are based on the use of an imaging star tracker. The methods are distinguished by the number of guidestars that are required per target, the amount of computational capability necessary, and the time required for the complete acquisition process. Each method is described in detail.

Detecting and Analyzing Corrosion Spots on the Hull of Large Marine Vessels Using Colored 3d LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Aijazi, A. K.; Malaterre, L.; Tazir, M. L.; Trassoudaine, L.; Checchin, P.

2016-06-01

This work presents a new method that automatically detects and analyzes surface defects such as corrosion spots of different shapes and sizes, on large ship hulls. In the proposed method several scans from different positions and viewing angles around the ship are registered together to form a complete 3D point cloud. The R, G, B values associated with each scan, obtained with the help of an integrated camera are converted into HSV space to separate out the illumination invariant color component from the intensity. Using this color component, different surface defects such as corrosion spots of different shapes and sizes are automatically detected, within a selected zone, using two different methods depending upon the level of corrosion/defects. The first method relies on a histogram based distribution whereas the second on adaptive thresholds. The detected corrosion spots are then analyzed and quantified to help better plan and estimate the cost of repair and maintenance. Results are evaluated on real data using different standard evaluation metrics to demonstrate the efficacy as well as the technical strength of the proposed method.

Hand held data collection and monitoring system for nuclear facilities

DOEpatents

Brayton, D.D.; Scharold, P.G.; Thornton, M.W.; Marquez, D.L.

1999-01-26

Apparatus and method is disclosed for a data collection and monitoring system that utilizes a pen based hand held computer unit which has contained therein interaction software that allows the user to review maintenance procedures, collect data, compare data with historical trends and safety limits, and input new information at various collection sites. The system has a means to allow automatic transfer of the collected data to a main computer data base for further review, reporting, and distribution purposes and uploading updated collection and maintenance procedures. The hand held computer has a running to-do list so sample collection and other general tasks, such as housekeeping are automatically scheduled for timely completion. A done list helps users to keep track of all completed tasks. The built-in check list assures that work process will meet the applicable processes and procedures. Users can hand write comments or drawings with an electronic pen that allows the users to directly interface information on the screen. 15 figs.

Hand held data collection and monitoring system for nuclear facilities

DOEpatents

Brayton, Darryl D.; Scharold, Paul G.; Thornton, Michael W.; Marquez, Diana L.

1999-01-01

Apparatus and method is disclosed for a data collection and monitoring system that utilizes a pen based hand held computer unit which has contained therein interaction software that allows the user to review maintenance procedures, collect data, compare data with historical trends and safety limits, and input new information at various collection sites. The system has a means to allow automatic transfer of the collected data to a main computer data base for further review, reporting, and distribution purposes and uploading updated collection and maintenance procedures. The hand held computer has a running to-do list so sample collection and other general tasks, such as housekeeping are automatically scheduled for timely completion. A done list helps users to keep track of all completed tasks. The built-in check list assures that work process will meet the applicable processes and procedures. Users can hand write comments or drawings with an electronic pen that allows the users to directly interface information on the screen.

Toward the automated generation of genome-scale metabolic networks in the SEED.

PubMed

DeJongh, Matthew; Formsma, Kevin; Boillot, Paul; Gould, John; Rycenga, Matthew; Best, Aaron

2007-04-26

Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis). We have implemented our tools and database within the SEED, an open-source software environment for comparative genome annotation and analysis. Our method sets the stage for the automated generation of substantially complete metabolic networks for over 400 complete genome sequences currently in the SEED. With each genome that is processed using our tools, the database of common components grows to cover more of the diversity of metabolic pathways. This increases the likelihood that components of reaction networks for subsequently processed genomes can be retrieved from the database, rather than assembled and verified manually.

Inference of segmented color and texture description by tensor voting.

PubMed

Jia, Jiaya; Tang, Chi-Keung

2004-06-01

A robust synthesis method is proposed to automatically infer missing color and texture information from a damaged 2D image by (N)D tensor voting (N > 3). The same approach is generalized to range and 3D data in the presence of occlusion, missing data and noise. Our method translates texture information into an adaptive (N)D tensor, followed by a voting process that infers noniteratively the optimal color values in the (N)D texture space. A two-step method is proposed. First, we perform segmentation based on insufficient geometry, color, and texture information in the input, and extrapolate partitioning boundaries by either 2D or 3D tensor voting to generate a complete segmentation for the input. Missing colors are synthesized using (N)D tensor voting in each segment. Different feature scales in the input are automatically adapted by our tensor scale analysis. Results on a variety of difficult inputs demonstrate the effectiveness of our tensor voting approach.

A simple node and conductor data generator for SINDA

NASA Technical Reports Server (NTRS)

Gottula, Ronald R.

1992-01-01

This paper presents a simple, automated method to generate NODE and CONDUCTOR DATA for thermal match modes. The method uses personal computer spreadsheets to create SINDA inputs. It was developed in order to make SINDA modeling less time consuming and serves as an alternative to graphical methods. Anyone having some experience using a personal computer can easily implement this process. The user develops spreadsheets to automatically calculate capacitances and conductances based on material properties and dimensional data. The necessary node and conductor information is then taken from the spreadsheets and automatically arranged into the proper format, ready for insertion directly into the SINDA model. This technique provides a number of benefits to the SINDA user such as a reduction in the number of hand calculations, and an ability to very quickly generate a parametric set of NODE and CONDUCTOR DATA blocks. It also provides advantages over graphical thermal modeling systems by retaining the analyst's complete visibility into the thermal network, and by permitting user comments anywhere within the DATA blocks.

Use of noncrystallographic symmetry for automated model building at medium to low resolution.

PubMed

Wiegels, Tim; Lamzin, Victor S

2012-04-01

A novel method is presented for the automatic detection of noncrystallographic symmetry (NCS) in macromolecular crystal structure determination which does not require the derivation of molecular masks or the segmentation of density. It was found that throughout structure determination the NCS-related parts may be differently pronounced in the electron density. This often results in the modelling of molecular fragments of variable length and accuracy, especially during automated model-building procedures. These fragments were used to identify NCS relations in order to aid automated model building and refinement. In a number of test cases higher completeness and greater accuracy of the obtained structures were achieved, specifically at a crystallographic resolution of 2.3 Å or poorer. In the best case, the method allowed the building of up to 15% more residues automatically and a tripling of the average length of the built fragments.

Automatic Scoring of Paper-and-Pencil Figural Responses. Research Report.

ERIC Educational Resources Information Center

Martinez, Michael E.; And Others

Large-scale testing is dominated by the multiple-choice question format. Widespread use of the format is due, in part, to the ease with which multiple-choice items can be scored automatically. This paper examines automatic scoring procedures for an alternative item type: figural response. Figural response items call for the completion or…

Applying the Quadruple Process Model to Evaluate Change in Implicit Attitudinal Responses During Therapy for Panic Disorder

PubMed Central

Clerkin, Elise M.; Fisher, Christopher R.; Sherman, Jeffrey W.; Teachman, Bethany A.

2013-01-01

Objective This study explored the automatic and controlled processes that may influence performance on an implicit measure across cognitive-behavioral group therapy for panic disorder. Method The Quadruple Process model was applied to error scores from an Implicit Association Test evaluating associations between the concepts Me (vs. Not Me) + Calm (vs. Panicked) to evaluate four distinct processes: Association Activation, Detection, Guessing, and Overcoming Bias. Parameter estimates were calculated in the panic group (n=28) across each treatment session where the IAT was administered, and at matched times when the IAT was completed in the healthy control group (n=31). Results Association Activation for Me + Calm became stronger over treatment for participants in the panic group, demonstrating that it is possible to change automatically activated associations in memory (vs. simply overriding those associations) in a clinical sample via therapy. As well, the Guessing bias toward the calm category increased over treatment for participants in the panic group. Conclusions This research evaluates key tenets about the role of automatic processing in cognitive models of anxiety, and emphasizes the viability of changing the actual activation of automatic associations in the context of treatment, versus only changing a person’s ability to use reflective processing to overcome biased automatic processing. PMID:24275066

Basic investigation of the laminated alginate impression technique: Setting time, permanent deformation, elastic deformation, consistency, and tensile bond strength tests.

PubMed

Kitamura, Aya; Kawai, Yasuhiko

2015-01-01

Laminated alginate impression for edentulous is simple and time efficient compared to border molding technique. The purpose of this study was to examine clinical applicability of the laminated alginate impression, by measuring the effects of different Water/Powder (W/P) and mixing methods, and different bonding methods in the secondary impression of alginate impression. Three W/P: manufacturer-designated mixing water amount (standard), 1.5-fold (1.5×) and 1.75-fold (1.75×) water amount were mixed by manual and automatic mixing methods. Initial and complete setting time, permanent and elastic deformation, and consistency of the secondary impression were investigated (n=10). Additionally, tensile bond strength between the primary and secondary impression were measured in the following surface treatment; air blow only (A), surface baking (B), and alginate impression material bonding agent (ALGI-BOND: AB) (n=12). Initial setting times significantly shortened with automatic mixing for all W/P (p<0.05). The permanent deformation decreased and elastic deformation increased as high W/P, regardless of the mixing method. Elastic deformation significantly reduced in 1.5× and 1.75× with automatic mixing (p<0.05). All of these properties resulted within JIS standards. For all W/P, AB showed a significantly high bonding strength as compared to A and B (p<0.01). The increase of mixing water, 1.5× and 1.75×, resulted within JIS standards in setting time, suggesting its applicability in clinical setting. The use of automatic mixing device decreased elastic strain and shortening of the curing time. For the secondary impression application of adhesives on the primary impression gives secure adhesion. Copyright © 2014 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.

Comparison of Airway Control Methods and Ventilation Success with an Automatic Resuscitator

DTIC Science & Technology

2015-10-08

REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour...completing and reviewing this collection of information . Send comments regarding this burden estimate or any other aspect of this collection of information ...including suggestions for reducing this burden to Department of Defense, Washington Headquarters Services, Directorate for Information Operations

Automatic calculation of the nine equivalents of nursing manpower use score (NEMS) using a patient data management system.

PubMed

Junger, Axel; Brenck, Florian; Hartmann, Bernd; Klasen, Joachim; Quinzio, Lorenzo; Benson, Matthias; Michel, Achim; Röhrig, Rainer; Hempelmann, Gunter

2004-07-01

The most recent approach to estimate nursing resources consumption has led to the generation of the Nine Equivalents of Nursing Manpower use Score (NEMS). The objective of this prospective study was to establish a completely automatically generated calculation of the NEMS using a patient data management system (PDMS) database and to validate this approach by comparing the results with those of the conventional manual method. Prospective study. Operative intensive care unit of a university hospital. Patients admitted to the ICU between 24 July 2002 and 22 August 2002. Patients under the age of 16 years, and patients undergoing cardiovascular surgery or with burn injuries were excluded. None. The NEMS of all patients was calculated automatically with a PDMS and manually by a physician in parallel. The results of the two methods were compared using the Bland and Altman approach, the interclass correlation coefficient (ICC), and the kappa-statistic. On 20 consecutive working days, the NEMS was calculated in 204 cases. The Bland Altman analysis did not show significant differences in NEMS scoring between the two methods. The ICC (95% confidence intervals) 0.87 (0.84-0.90) revealed a high inter-rater agreement between the PDMS and the physician. The kappa-statistic showed good results (kappa>0.55) for all NEMS items apart from the item "supplementary ventilatory care". This study demonstrates that automatical calculation of the NEMS is possible with high accuracy by means of a PDMS. This may lead to a decrease in consumption of nursing resources.

Comparison of landmark-based and automatic methods for cortical surface registration

PubMed Central

Pantazis, Dimitrios; Joshi, Anand; Jiang, Jintao; Shattuck, David; Bernstein, Lynne E.; Damasio, Hanna; Leahy, Richard M.

2009-01-01

Group analysis of structure or function in cerebral cortex typically involves as a first step the alignment of the cortices. A surface based approach to this problem treats the cortex as a convoluted surface and coregisters across subjects so that cortical landmarks or features are aligned. This registration can be performed using curves representing sulcal fundi and gyral crowns to constrain the mapping. Alternatively, registration can be based on the alignment of curvature metrics computed over the entire cortical surface. The former approach typically involves some degree of user interaction in defining the sulcal and gyral landmarks while the latter methods can be completely automated. Here we introduce a cortical delineation protocol consisting of 26 consistent landmarks spanning the entire cortical surface. We then compare the performance of a landmark-based registration method that uses this protocol with that of two automatic methods implemented in the software packages FreeSurfer and BrainVoyager. We compare performance in terms of discrepancy maps between the different methods, the accuracy with which regions of interest are aligned, and the ability of the automated methods to correctly align standard cortical landmarks. Our results show similar performance for ROIs in the perisylvian region for the landmark based method and FreeSurfer. However, the discrepancy maps showed larger variability between methods in occipital and frontal cortex and also that automated methods often produce misalignment of standard cortical landmarks. Consequently, selection of the registration approach should consider the importance of accurate sulcal alignment for the specific task for which coregistration is being performed. When automatic methods are used, the users should ensure that sulci in regions of interest in their studies are adequately aligned before proceeding with subsequent analysis. PMID:19796696

Bayesian CP Factorization of Incomplete Tensors with Automatic Rank Determination.

PubMed

Zhao, Qibin; Zhang, Liqing; Cichocki, Andrzej

2015-09-01

CANDECOMP/PARAFAC (CP) tensor factorization of incomplete data is a powerful technique for tensor completion through explicitly capturing the multilinear latent factors. The existing CP algorithms require the tensor rank to be manually specified, however, the determination of tensor rank remains a challenging problem especially for CP rank . In addition, existing approaches do not take into account uncertainty information of latent factors, as well as missing entries. To address these issues, we formulate CP factorization using a hierarchical probabilistic model and employ a fully Bayesian treatment by incorporating a sparsity-inducing prior over multiple latent factors and the appropriate hyperpriors over all hyperparameters, resulting in automatic rank determination. To learn the model, we develop an efficient deterministic Bayesian inference algorithm, which scales linearly with data size. Our method is characterized as a tuning parameter-free approach, which can effectively infer underlying multilinear factors with a low-rank constraint, while also providing predictive distributions over missing entries. Extensive simulations on synthetic data illustrate the intrinsic capability of our method to recover the ground-truth of CP rank and prevent the overfitting problem, even when a large amount of entries are missing. Moreover, the results from real-world applications, including image inpainting and facial image synthesis, demonstrate that our method outperforms state-of-the-art approaches for both tensor factorization and tensor completion in terms of predictive performance.

Assessment of Automatically Exported Clinical Data from a Hospital Information System for Clinical Research in Multiple Myeloma.

PubMed

Torres, Viviana; Cerda, Mauricio; Knaup, Petra; Löpprich, Martin

2016-01-01

An important part of the electronic information available in Hospital Information System (HIS) has the potential to be automatically exported to Electronic Data Capture (EDC) platforms for improving clinical research. This automation has the advantage of reducing manual data transcription, a time consuming and prone to errors process. However, quantitative evaluations of the process of exporting data from a HIS to an EDC system have not been reported extensively, in particular comparing with manual transcription. In this work an assessment to study the quality of an automatic export process, focused in laboratory data from a HIS is presented. Quality of the laboratory data was assessed in two types of processes: (1) a manual process of data transcription, and (2) an automatic process of data transference. The automatic transference was implemented as an Extract, Transform and Load (ETL) process. Then, a comparison was carried out between manual and automatic data collection methods. The criteria to measure data quality were correctness and completeness. The manual process had a general error rate of 2.6% to 7.1%, obtaining the lowest error rate if data fields with a not clear definition were removed from the analysis (p < 10E-3). In the case of automatic process, the general error rate was 1.9% to 12.1%, where lowest error rate is obtained when excluding information missing in the HIS but transcribed to the EDC from other physical sources. The automatic ETL process can be used to collect laboratory data for clinical research if data in the HIS as well as physical documentation not included in HIS, are identified previously and follows a standardized data collection protocol.

Validation of the ICU-DaMa tool for automatically extracting variables for minimum dataset and quality indicators: The importance of data quality assessment.

PubMed

Sirgo, Gonzalo; Esteban, Federico; Gómez, Josep; Moreno, Gerard; Rodríguez, Alejandro; Blanch, Lluis; Guardiola, Juan José; Gracia, Rafael; De Haro, Lluis; Bodí, María

2018-04-01

Big data analytics promise insights into healthcare processes and management, improving outcomes while reducing costs. However, data quality is a major challenge for reliable results. Business process discovery techniques and an associated data model were used to develop data management tool, ICU-DaMa, for extracting variables essential for overseeing the quality of care in the intensive care unit (ICU). To determine the feasibility of using ICU-DaMa to automatically extract variables for the minimum dataset and ICU quality indicators from the clinical information system (CIS). The Wilcoxon signed-rank test and Fisher's exact test were used to compare the values extracted from the CIS with ICU-DaMa for 25 variables from all patients attended in a polyvalent ICU during a two-month period against the gold standard of values manually extracted by two trained physicians. Discrepancies with the gold standard were classified into plausibility, conformance, and completeness errors. Data from 149 patients were included. Although there were no significant differences between the automatic method and the manual method, we detected differences in values for five variables, including one plausibility error and two conformance and completeness errors. Plausibility: 1) Sex, ICU-DaMa incorrectly classified one male patient as female (error generated by the Hospital's Admissions Department). Conformance: 2) Reason for isolation, ICU-DaMa failed to detect a human error in which a professional misclassified a patient's isolation. 3) Brain death, ICU-DaMa failed to detect another human error in which a professional likely entered two mutually exclusive values related to the death of the patient (brain death and controlled donation after circulatory death). Completeness: 4) Destination at ICU discharge, ICU-DaMa incorrectly classified two patients due to a professional failing to fill out the patient discharge form when thepatients died. 5) Length of continuous renal replacement therapy, data were missing for one patient because the CRRT device was not connected to the CIS. Automatic generation of minimum dataset and ICU quality indicators using ICU-DaMa is feasible. The discrepancies were identified and can be corrected by improving CIS ergonomics, training healthcare professionals in the culture of the quality of information, and using tools for detecting and correcting data errors. Copyright © 2018 Elsevier B.V. All rights reserved.

Design and realization of an automatic weather station at island

NASA Astrophysics Data System (ADS)

Chen, Yong-hua; Li, Si-ren

2011-10-01

In this paper, the design and development of an automatic weather station monitoring is described. The proposed system consists of a set of sensors for measuring meteorological parameters (temperature, wind speed & direction, rain fall, visibility, etc.). To increase the reliability of the system, wind speed & direction are measured redundantly with duplicate sensors. The sensor signals are collected by the data logger CR1000 at several analog and digital inputs. The CR1000 and the sensors form a completely autonomous system which works with the other systems installed in the container. Communication with the master PC is accomplished over the method of Code Division Multiple Access (CDMA) with the Compact Caimore6550P CDMA DTU. The data are finally stored in tables on the CPU as well as on the CF-Card. The weather station was built as an efficient autonomous system which operates with the other systems to provide the required data for a fully automatic measurement system.

Kinase Pathway Database: An Integrated Protein-Kinase and NLP-Based Protein-Interaction Resource

PubMed Central

Koike, Asako; Kobayashi, Yoshiyuki; Takagi, Toshihisa

2003-01-01

Protein kinases play a crucial role in the regulation of cellular functions. Various kinds of information about these molecules are important for understanding signaling pathways and organism characteristics. We have developed the Kinase Pathway Database, an integrated database involving major completely sequenced eukaryotes. It contains the classification of protein kinases and their functional conservation, ortholog tables among species, protein–protein, protein–gene, and protein–compound interaction data, domain information, and structural information. It also provides an automatic pathway graphic image interface. The protein, gene, and compound interactions are automatically extracted from abstracts for all genes and proteins by natural-language processing (NLP).The method of automatic extraction uses phrase patterns and the GENA protein, gene, and compound name dictionary, which was developed by our group. With this database, pathways are easily compared among species using data with more than 47,000 protein interactions and protein kinase ortholog tables. The database is available for querying and browsing at http://kinasedb.ontology.ims.u-tokyo.ac.jp/. PMID:12799355

Spatiotemporal evolution of the completeness magnitude of the Icelandic earthquake catalogue from 1991 to 2013

NASA Astrophysics Data System (ADS)

Panzera, Francesco; Mignan, Arnaud; Vogfjörð, Kristin S.

2017-07-01

In 1991, a digital seismic monitoring network was installed in Iceland with a digital seismic system and automatic operation. After 20 years of operation, we explore for the first time its nationwide performance by analysing the spatiotemporal variations of the completeness magnitude. We use the Bayesian magnitude of completeness (BMC) method that combines local completeness magnitude observations with prior information based on the density of seismic stations. Additionally, we test the impact of earthquake location uncertainties on the BMC results, by filtering the catalogue using a multivariate analysis that identifies outliers in the hypocentre error distribution. We find that the entire North-to-South active rift zone shows a relatively low magnitude of completeness Mc in the range 0.5-1.0, highlighting the ability of the Icelandic network to detect small earthquakes. This work also demonstrates the influence of earthquake location uncertainties on the spatiotemporal magnitude of completeness analysis.

Kinematics modeling and experimentation of the multi-manipulator tooth-arrangement robot for full denture manufacturing.

PubMed

Zhang, Yong-de; Jiang, Jin-gang; Liang, Ting; Hu, Wei-ping

2011-12-01

Artificial teeth are very complicated in shape, and not easy to be grasped and manipulated accurately by a single robot. The method of tooth-arrangement by multi-manipulator for complete denture manufacturing proposed in this paper. A novel complete denture manufacturing mechanism is designed based on multi-manipulator and dental arch generator. Kinematics model of the multi-manipulator tooth-arrangement robot is built by analytical method based on tooth-arrangement principle for full denture. Preliminary experiments on tooth-arrangement are performed using the multi-manipulator tooth-arrangement robot prototype system. The multi-manipulator tooth-arrangement robot prototype system can automatically design and manufacture a set of complete denture that is suitable for a patient according to the jaw arch parameters. The experimental results verified the validity of kinematics model of the multi-manipulator tooth-arrangement robot and the feasibility of the manufacture strategy of complete denture fulfilled by multi-manipulator tooth-arrangement robot.

Reproducing the internal and external anatomy of fossil bones: Two new automatic digital tools.

PubMed

Profico, Antonio; Schlager, Stefan; Valoriani, Veronica; Buzi, Costantino; Melchionna, Marina; Veneziano, Alessio; Raia, Pasquale; Moggi-Cecchi, Jacopo; Manzi, Giorgio

2018-04-21

We present two new automatic tools, developed under the R environment, to reproduce the internal and external structures of bony elements. The first method, Computer-Aided Laser Scanner Emulator (CA-LSE), provides the reconstruction of the external portions of a 3D mesh by simulating the action of a laser scanner. The second method, Automatic Segmentation Tool for 3D objects (AST-3D), performs the digital reconstruction of anatomical cavities. We present the application of CA-LSE and AST-3D methods to different anatomical remains, highly variable in terms of shape, size and structure: a modern human skull, a malleus bone, and a Neanderthal deciduous tooth. Both methods are developed in the R environment and embedded in the packages "Arothron" and "Morpho," where both the codes and the data are fully available. The application of CA-LSE and AST-3D allows the isolation and manipulation of the internal and external components of the 3D virtual representation of complex bony elements. In particular, we present the output of the four case studies: a complete modern human endocast and the right maxillary sinus, the dental pulp of the Neanderthal tooth and the inner network of blood vessels of the malleus. Both methods demonstrated to be much faster, cheaper, and more accurate than other conventional approaches. The tools we presented are available as add-ons in existing software within the R platform. Because of ease of application, and unrestrained availability of the methods proposed, these tools can be widely used by paleoanthropologists, paleontologists and anatomists. © 2018 Wiley Periodicals, Inc.

Regulation and Measurement of the Heat Generated by Automatic Tooth Preparation in a Confined Space.

PubMed

Yuan, Fusong; Zheng, Jianqiao; Sun, Yuchun; Wang, Yong; Lyu, Peijun

2017-06-01

The aim of this study was to assess and regulate heat generation in the dental pulp cavity and circumambient temperature around a tooth during laser ablation with a femtosecond laser in a confined space. The automatic tooth preparing technique is one of the traditional oral clinical technology innovations. In this technique, a robot controlled an ultrashort pulse laser to automatically complete the three-dimensional teeth preparing in a confined space. The temperature control is the main measure for protecting the tooth nerve. Ten tooth specimens were irradiated with a femtosecond laser controlled by a robot in a confined space to generate 10 teeth preparation. During the process, four thermocouple sensors were used to record the pulp cavity and circumambient environment temperatures with or without air cooling. A statistical analysis of the temperatures was performed between the conditions with and without air cooling (p < 0.05). The recordings showed that the temperature with air cooling was lower than that without air cooling and that the heat generated in the pulp cavity was lower than the threshold for dental pulp damage. These results indicate that femtosecond laser ablation with air cooling might be an appropriate method for automatic tooth preparing.

A comparison of conscious and automatic memory processes for picture and word stimuli: a process dissociation analysis.

PubMed

McBride, Dawn M; Anne Dosher, Barbara

2002-09-01

Four experiments were conducted to evaluate explanations of picture superiority effects previously found for several tasks. In a process dissociation procedure (Jacoby, 1991) with word stem completion, picture fragment completion, and category production tasks, conscious and automatic memory processes were compared for studied pictures and words with an independent retrieval model and a generate-source model. The predictions of a transfer appropriate processing account of picture superiority were tested and validated in "process pure" latent measures of conscious and unconscious, or automatic and source, memory processes. Results from both model fits verified that pictures had a conceptual (conscious/source) processing advantage over words for all tasks. The effects of perceptual (automatic/word generation) compatibility depended on task type, with pictorial tasks favoring pictures and linguistic tasks favoring words. Results show support for an explanation of the picture superiority effect that involves an interaction of encoding and retrieval processes.

Comparison of automatic and visual methods used for image segmentation in Endodontics: a microCT study.

PubMed

Queiroz, Polyane Mazucatto; Rovaris, Karla; Santaella, Gustavo Machado; Haiter-Neto, Francisco; Freitas, Deborah Queiroz

2017-01-01

To calculate root canal volume and surface area in microCT images, an image segmentation by selecting threshold values is required, which can be determined by visual or automatic methods. Visual determination is influenced by the operator's visual acuity, while the automatic method is done entirely by computer algorithms. To compare between visual and automatic segmentation, and to determine the influence of the operator's visual acuity on the reproducibility of root canal volume and area measurements. Images from 31 extracted human anterior teeth were scanned with a μCT scanner. Three experienced examiners performed visual image segmentation, and threshold values were recorded. Automatic segmentation was done using the "Automatic Threshold Tool" available in the dedicated software provided by the scanner's manufacturer. Volume and area measurements were performed using the threshold values determined both visually and automatically. The paired Student's t-test showed no significant difference between visual and automatic segmentation methods regarding root canal volume measurements (p=0.93) and root canal surface (p=0.79). Although visual and automatic segmentation methods can be used to determine the threshold and calculate root canal volume and surface, the automatic method may be the most suitable for ensuring the reproducibility of threshold determination.

MO-G-BRE-04: Automatic Verification of Daily Treatment Deliveries and Generation of Daily Treatment Reports for a MR Image-Guided Treatment Machine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, D; Li, X; Li, H

2014-06-15

Purpose: Two aims of this work were to develop a method to automatically verify treatment delivery accuracy immediately after patient treatment and to develop a comprehensive daily treatment report to provide all required information for daily MR-IGRT review. Methods: After systematically analyzing the requirements for treatment delivery verification and understanding the available information from a novel MR-IGRT treatment machine, we designed a method to use 1) treatment plan files, 2) delivery log files, and 3) dosimetric calibration information to verify the accuracy and completeness of daily treatment deliveries. The method verifies the correctness of delivered treatment plans and beams, beammore » segments, and for each segment, the beam-on time and MLC leaf positions. Composite primary fluence maps are calculated from the MLC leaf positions and the beam-on time. Error statistics are calculated on the fluence difference maps between the plan and the delivery. We also designed the daily treatment delivery report by including all required information for MR-IGRT and physics weekly review - the plan and treatment fraction information, dose verification information, daily patient setup screen captures, and the treatment delivery verification results. Results: The parameters in the log files (e.g. MLC positions) were independently verified and deemed accurate and trustable. A computer program was developed to implement the automatic delivery verification and daily report generation. The program was tested and clinically commissioned with sufficient IMRT and 3D treatment delivery data. The final version has been integrated into a commercial MR-IGRT treatment delivery system. Conclusion: A method was developed to automatically verify MR-IGRT treatment deliveries and generate daily treatment reports. Already in clinical use since December 2013, the system is able to facilitate delivery error detection, and expedite physician daily IGRT review and physicist weekly chart review.« less

Left ventricular endocardial surface detection based on real-time 3D echocardiographic data

NASA Technical Reports Server (NTRS)

Corsi, C.; Borsari, M.; Consegnati, F.; Sarti, A.; Lamberti, C.; Travaglini, A.; Shiota, T.; Thomas, J. D.

2001-01-01

OBJECTIVE: A new computerized semi-automatic method for left ventricular (LV) chamber segmentation is presented. METHODS: The LV is imaged by real-time three-dimensional echocardiography (RT3DE). The surface detection model, based on level set techniques, is applied to RT3DE data for image analysis. The modified level set partial differential equation we use is solved by applying numerical methods for conservation laws. The initial conditions are manually established on some slices of the entire volume. The solution obtained for each slice is a contour line corresponding with the boundary between LV cavity and LV endocardium. RESULTS: The mathematical model has been applied to sequences of frames of human hearts (volume range: 34-109 ml) imaged by 2D and reconstructed off-line and RT3DE data. Volume estimation obtained by this new semi-automatic method shows an excellent correlation with those obtained by manual tracing (r = 0.992). Dynamic change of LV volume during the cardiac cycle is also obtained. CONCLUSION: The volume estimation method is accurate; edge based segmentation, image completion and volume reconstruction can be accomplished. The visualization technique also allows to navigate into the reconstructed volume and to display any section of the volume.

Systems, methods and apparatus for generation and verification of policies in autonomic computing systems

NASA Technical Reports Server (NTRS)

Rouff, Christopher A. (Inventor); Sterritt, Roy (Inventor); Truszkowski, Walter F. (Inventor); Hinchey, Michael G. (Inventor); Gracanin, Denis (Inventor); Rash, James L. (Inventor)

2011-01-01

Described herein is a method that produces fully (mathematically) tractable development of policies for autonomic systems from requirements through to code generation. This method is illustrated through an example showing how user formulated policies can be translated into a formal mode which can then be converted to code. The requirements-based programming method described provides faster, higher quality development and maintenance of autonomic systems based on user formulation of policies.Further, the systems, methods and apparatus described herein provide a way of analyzing policies for autonomic systems and facilities the generation of provably correct implementations automatically, which in turn provides reduced development time, reduced testing requirements, guarantees of correctness of the implementation with respect to the policies specified at the outset, and provides a higher degree of confidence that the policies are both complete and reasonable. The ability to specify the policy for the management of a system and then automatically generate an equivalent implementation greatly improves the quality of software, the survivability of future missions, in particular when the system will operate untended in very remote environments, and greatly reduces development lead times and costs.

An automatic method to detect and track the glottal gap from high speed videoendoscopic images.

PubMed

Andrade-Miranda, Gustavo; Godino-Llorente, Juan I; Moro-Velázquez, Laureano; Gómez-García, Jorge Andrés

2015-10-29

The image-based analysis of the vocal folds vibration plays an important role in the diagnosis of voice disorders. The analysis is based not only on the direct observation of the video sequences, but also in an objective characterization of the phonation process by means of features extracted from the recorded images. However, such analysis is based on a previous accurate identification of the glottal gap, which is the most challenging step for a further automatic assessment of the vocal folds vibration. In this work, a complete framework to automatically segment and track the glottal area (or glottal gap) is proposed. The algorithm identifies a region of interest that is adapted along time, and combine active contours and watershed transform for the final delineation of the glottis and also an automatic procedure for synthesize different videokymograms is proposed. Thanks to the ROI implementation, our technique is robust to the camera shifting and also the objective test proved the effectiveness and performance of the approach in the most challenging scenarios that it is when exist an inappropriate closure of the vocal folds. The novelties of the proposed algorithm relies on the used of temporal information for identify an adaptive ROI and the use of watershed merging combined with active contours for the glottis delimitation. Additionally, an automatic procedure for synthesize multiline VKG by the identification of the glottal main axis is developed.

Semi-Automatic Modelling of Building FAÇADES with Shape Grammars Using Historic Building Information Modelling

NASA Astrophysics Data System (ADS)

Dore, C.; Murphy, M.

2013-02-01

This paper outlines a new approach for generating digital heritage models from laser scan or photogrammetric data using Historic Building Information Modelling (HBIM). HBIM is a plug-in for Building Information Modelling (BIM) software that uses parametric library objects and procedural modelling techniques to automate the modelling stage. The HBIM process involves a reverse engineering solution whereby parametric interactive objects representing architectural elements are mapped onto laser scan or photogrammetric survey data. A library of parametric architectural objects has been designed from historic manuscripts and architectural pattern books. These parametric objects were built using an embedded programming language within the ArchiCAD BIM software called Geometric Description Language (GDL). Procedural modelling techniques have been implemented with the same language to create a parametric building façade which automatically combines library objects based on architectural rules and proportions. Different configurations of the façade are controlled by user parameter adjustment. The automatically positioned elements of the façade can be subsequently refined using graphical editing while overlaying the model with orthographic imagery. Along with this semi-automatic method for generating façade models, manual plotting of library objects can also be used to generate a BIM model from survey data. After the 3D model has been completed conservation documents such as plans, sections, elevations and 3D views can be automatically generated for conservation projects.

Can a CNN recognize Catalan diet?

NASA Astrophysics Data System (ADS)

Herruzo, P.; Bolaños, M.; Radeva, P.

2016-10-01

Nowadays, we can find several diseases related to the unhealthy diet habits of the population, such as diabetes, obesity, anemia, bulimia and anorexia. In many cases, these diseases are related to the food consumption of people. Mediterranean diet is scientifically known as a healthy diet that helps to prevent many metabolic diseases. In particular, our work focuses on the recognition of Mediterranean food and dishes. The development of this methodology would allow to analise the daily habits of users with wearable cameras, within the topic of lifelogging. By using automatic mechanisms we could build an objective tool for the analysis of the patient's behavior, allowing specialists to discover unhealthy food patterns and understand the user's lifestyle. With the aim to automatically recognize a complete diet, we introduce a challenging multi-labeled dataset related to Mediter-ranean diet called FoodCAT. The first type of label provided consists of 115 food classes with an average of 400 images per dish, and the second one consists of 12 food categories with an average of 3800 pictures per class. This dataset will serve as a basis for the development of automatic diet recognition. In this context, deep learning and more specifically, Convolutional Neural Networks (CNNs), currently are state-of-the-art methods for automatic food recognition. In our work, we compare several architectures for image classification, with the purpose of diet recognition. Applying the best model for recognising food categories, we achieve a top-1 accuracy of 72.29%, and top-5 of 97.07%. In a complete diet recognition of dishes from Mediterranean diet, enlarged with the Food-101 dataset for international dishes recognition, we achieve a top-1 accuracy of 68.07%, and top-5 of 89.53%, for a total of 115+101 food classes.

Uncertain Classification of Variable Stars: Handling Observational GAPS and Noise

NASA Astrophysics Data System (ADS)

Castro, Nicolás; Protopapas, Pavlos; Pichara, Karim

2018-01-01

Automatic classification methods applied to sky surveys have revolutionized the astronomical target selection process. Most surveys generate a vast amount of time series, or “lightcurves,” that represent the brightness variability of stellar objects in time. Unfortunately, lightcurves’ observations take several years to be completed, producing truncated time series that generally remain without the application of automatic classifiers until they are finished. This happens because state-of-the-art methods rely on a variety of statistical descriptors or features that present an increasing degree of dispersion when the number of observations decreases, which reduces their precision. In this paper, we propose a novel method that increases the performance of automatic classifiers of variable stars by incorporating the deviations that scarcity of observations produces. Our method uses Gaussian process regression to form a probabilistic model of each lightcurve’s observations. Then, based on this model, bootstrapped samples of the time series features are generated. Finally, a bagging approach is used to improve the overall performance of the classification. We perform tests on the MAssive Compact Halo Object (MACHO) and Optical Gravitational Lensing Experiment (OGLE) catalogs, results show that our method effectively classifies some variability classes using a small fraction of the original observations. For example, we found that RR Lyrae stars can be classified with ~80% accuracy just by observing the first 5% of the whole lightcurves’ observations in the MACHO and OGLE catalogs. We believe these results prove that, when studying lightcurves, it is important to consider the features’ error and how the measurement process impacts it.

Automatic Detection and Reproduction of Natural Head Position in Stereo-Photogrammetry.

PubMed

Hsung, Tai-Chiu; Lo, John; Li, Tik-Shun; Cheung, Lim-Kwong

2015-01-01

The aim of this study was to develop an automatic orientation calibration and reproduction method for recording the natural head position (NHP) in stereo-photogrammetry (SP). A board was used as the physical reference carrier for true verticals and NHP alignment mirror orientation. Orientation axes were detected and saved from the digital mesh model of the board. They were used for correcting the pitch, roll and yaw angles of the subsequent captures of patients' facial surfaces, which were obtained without any markings or sensors attached onto the patient. We tested the proposed method on two commercial active (3dMD) and passive (DI3D) SP devices. The reliability of the pitch, roll and yaw for the board placement were within ±0.039904°, ±0.081623°, and ±0.062320°; where standard deviations were 0.020234°, 0.045645° and 0.027211° respectively. Orientation-calibrated stereo-photogrammetry is the most accurate method (angulation deviation within ±0.1°) reported for complete NHP recording with insignificant clinical error.

Automatic Detection and Reproduction of Natural Head Position in Stereo-Photogrammetry

PubMed Central

Hsung, Tai-Chiu; Lo, John; Li, Tik-Shun; Cheung, Lim-Kwong

2015-01-01

The aim of this study was to develop an automatic orientation calibration and reproduction method for recording the natural head position (NHP) in stereo-photogrammetry (SP). A board was used as the physical reference carrier for true verticals and NHP alignment mirror orientation. Orientation axes were detected and saved from the digital mesh model of the board. They were used for correcting the pitch, roll and yaw angles of the subsequent captures of patients’ facial surfaces, which were obtained without any markings or sensors attached onto the patient. We tested the proposed method on two commercial active (3dMD) and passive (DI3D) SP devices. The reliability of the pitch, roll and yaw for the board placement were within ±0.039904°, ±0.081623°, and ±0.062320°; where standard deviations were 0.020234°, 0.045645° and 0.027211° respectively. Conclusion: Orientation-calibrated stereo-photogrammetry is the most accurate method (angulation deviation within ±0.1°) reported for complete NHP recording with insignificant clinical error. PMID:26125616

Automated Mobile System for Accurate Outdoor Tree Crop Enumeration Using an Uncalibrated Camera.

PubMed

Nguyen, Thuy Tuong; Slaughter, David C; Hanson, Bradley D; Barber, Andrew; Freitas, Amy; Robles, Daniel; Whelan, Erin

2015-07-28

This paper demonstrates an automated computer vision system for outdoor tree crop enumeration in a seedling nursery. The complete system incorporates both hardware components (including an embedded microcontroller, an odometry encoder, and an uncalibrated digital color camera) and software algorithms (including microcontroller algorithms and the proposed algorithm for tree crop enumeration) required to obtain robust performance in a natural outdoor environment. The enumeration system uses a three-step image analysis process based upon: (1) an orthographic plant projection method integrating a perspective transform with automatic parameter estimation; (2) a plant counting method based on projection histograms; and (3) a double-counting avoidance method based on a homography transform. Experimental results demonstrate the ability to count large numbers of plants automatically with no human effort. Results show that, for tree seedlings having a height up to 40 cm and a within-row tree spacing of approximately 10 cm, the algorithms successfully estimated the number of plants with an average accuracy of 95.2% for trees within a single image and 98% for counting of the whole plant population in a large sequence of images.

Automated Mobile System for Accurate Outdoor Tree Crop Enumeration Using an Uncalibrated Camera

PubMed Central

Nguyen, Thuy Tuong; Slaughter, David C.; Hanson, Bradley D.; Barber, Andrew; Freitas, Amy; Robles, Daniel; Whelan, Erin

2015-01-01

This paper demonstrates an automated computer vision system for outdoor tree crop enumeration in a seedling nursery. The complete system incorporates both hardware components (including an embedded microcontroller, an odometry encoder, and an uncalibrated digital color camera) and software algorithms (including microcontroller algorithms and the proposed algorithm for tree crop enumeration) required to obtain robust performance in a natural outdoor environment. The enumeration system uses a three-step image analysis process based upon: (1) an orthographic plant projection method integrating a perspective transform with automatic parameter estimation; (2) a plant counting method based on projection histograms; and (3) a double-counting avoidance method based on a homography transform. Experimental results demonstrate the ability to count large numbers of plants automatically with no human effort. Results show that, for tree seedlings having a height up to 40 cm and a within-row tree spacing of approximately 10 cm, the algorithms successfully estimated the number of plants with an average accuracy of 95.2% for trees within a single image and 98% for counting of the whole plant population in a large sequence of images. PMID:26225982

Automatic segmentation and centroid detection of skin sensors for lung interventions

NASA Astrophysics Data System (ADS)

Lu, Kongkuo; Xu, Sheng; Xue, Zhong; Wong, Stephen T.

2012-02-01

Electromagnetic (EM) tracking has been recognized as a valuable tool for locating the interventional devices in procedures such as lung and liver biopsy or ablation. The advantage of this technology is its real-time connection to the 3D volumetric roadmap, i.e. CT, of a patient's anatomy while the intervention is performed. EM-based guidance requires tracking of the tip of the interventional device, transforming the location of the device onto pre-operative CT images, and superimposing the device in the 3D images to assist physicians to complete the procedure more effectively. A key requirement of this data integration is to find automatically the mapping between EM and CT coordinate systems. Thus, skin fiducial sensors are attached to patients before acquiring the pre-operative CTs. Then, those sensors can be recognized in both CT and EM coordinate systems and used calculate the transformation matrix. In this paper, to enable the EM-based navigation workflow and reduce procedural preparation time, an automatic fiducial detection method is proposed to obtain the centroids of the sensors from the pre-operative CT. The approach has been applied to 13 rabbit datasets derived from an animal study and eight human images from an observation study. The numerical results show that it is a reliable and efficient method for use in EM-guided application.

Automatic Commercial Permit Sets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grana, Paul

Final report for Folsom Labs’ Solar Permit Generator project, which has successfully completed, resulting in the development and commercialization of a software toolkit within the cloud-based HelioScope software environment that enables solar engineers to automatically generate and manage draft documents for permit submission.

Application of the Repetitions in Reserve-Based Rating of Perceived Exertion Scale for Resistance Training

PubMed Central

Cronin, John; Storey, Adam; Zourdos, Michael C.

2016-01-01

ABSTRACT RATINGS OF PERCEIVED EXERTION ARE A VALID METHOD OF ESTIMATING THE INTENSITY OF A RESISTANCE TRAINING EXERCISE OR SESSION. SCORES ARE GIVEN AFTER COMPLETION OF AN EXERCISE OR TRAINING SESSION FOR THE PURPOSES OF ATHLETE MONITORING. HOWEVER, A NEWLY DEVELOPED SCALE BASED ON HOW MANY REPETITIONS ARE REMAINING AT THE COMPLETION OF A SET MAY BE A MORE PRECISE TOOL. THIS APPROACH ADJUSTS LOADS AUTOMATICALLY TO MATCH ATHLETE CAPABILITIES ON A SET-TO-SET BASIS AND MAY MORE ACCURATELY GAUGE INTENSITY AT NEAR-LIMIT LOADS. THIS ARTICLE OUTLINES HOW TO INCORPORATE THIS NOVEL SCALE INTO A TRAINING PLAN. PMID:27531969

Micro-Raman spectroscopy: The analysis of micrometer and submicrometer atmospheric aerosols

NASA Technical Reports Server (NTRS)

Klainer, S. M.; Milanovich, F. P.

1985-01-01

A nondestructive method of molecular analysis which is required to fully utilize the information contained within a collected particle is discussed. Upper atmosphere reaction mechanisms are assessed when the chemical compounds, the use of micro-Raman spectrometric techniques to perform micron and submicron particle analysis was evaluated. The results are favorable and it is concluded that micron and submicron particles can be analyzed by the micron-Raman approach. Completely automatic analysis should be possible to 0.3 micro m. No problems are anticipated with photo or thermal decomposition. Sample and impurity fluorescence are the key source of background as they cannot be completely eliminated.

Structure Design and Realization of Rapid Medicine Dispensing System

NASA Astrophysics Data System (ADS)

Liu, Xiangquan

In this paper, the main components and function of rapid medicine dispensing system is analyzed, structure design of automatic feeding device, sloping storeroom, automatic dispensing device and automatic sorting device is completed. The system adopts medicine conveyer working in with manipulator to realize automatic batch supply of the boxed medicine, adopts sloping storeroom as warehouse of medicine to realize dense depositing, adopts dispensing mechanism which includes elevator, turning panel and electric magnet to realize rapid medicine dispensing, adopts sorting conveyor belt and sorting device to send medicine to designated outlet.

Automatic 1H-NMR Screening of Fatty Acid Composition in Edible Oils

PubMed Central

Castejón, David; Fricke, Pascal; Cambero, María Isabel; Herrera, Antonio

2016-01-01

In this work, we introduce an NMR-based screening method for the fatty acid composition analysis of edible oils. We describe the evaluation and optimization needed for the automated analysis of vegetable oils by low-field NMR to obtain the fatty acid composition (FAC). To achieve this, two scripts, which automatically analyze and interpret the spectral data, were developed. The objective of this work was to drive forward the automated analysis of the FAC by NMR. Due to the fact that this protocol can be carried out at low field and that the complete process from sample preparation to printing the report only takes about 3 min, this approach is promising to become a fundamental technique for high-throughput screening. To demonstrate the applicability of this method, the fatty acid composition of extra virgin olive oils from various Spanish olive varieties (arbequina, cornicabra, hojiblanca, manzanilla, and picual) was determined by 1H-NMR spectroscopy according to this protocol. PMID:26891323

Second sound tracking system

NASA Astrophysics Data System (ADS)

Yang, Jihee; Ihas, Gary G.; Ekdahl, Dan

2017-10-01

It is common that a physical system resonates at a particular frequency, whose frequency depends on physical parameters which may change in time. Often, one would like to automatically track this signal as the frequency changes, measuring, for example, its amplitude. In scientific research, one would also like to utilize the standard methods, such as lock-in amplifiers, to improve the signal to noise ratio. We present a complete He ii second sound system that uses positive feedback to generate a sinusoidal signal of constant amplitude via automatic gain control. This signal is used to produce temperature/entropy waves (second sound) in superfluid helium-4 (He ii). A lock-in amplifier limits the oscillation to a desirable frequency and demodulates the received sound signal. Using this tracking system, a second sound signal probed turbulent decay in He ii. We present results showing that the tracking system is more reliable than those of a conventional fixed frequency method; there is less correlation with temperature (frequency) fluctuation when the tracking system is used.

An automatic detection method for the boiler pipe header based on real-time image acquisition

NASA Astrophysics Data System (ADS)

Long, Yi; Liu, YunLong; Qin, Yongliang; Yang, XiangWei; Li, DengKe; Shen, DingJie

2017-06-01

Generally, an endoscope is used to test the inner part of the thermal power plants boiler pipe header. However, since the endoscope hose manual operation, the length and angle of the inserted probe cannot be controlled. Additionally, it has a big blind spot observation subject to the length of the endoscope wire. To solve these problems, an automatic detection method for the boiler pipe header based on real-time image acquisition and simulation comparison techniques was proposed. The magnetic crawler with permanent magnet wheel could carry the real-time image acquisition device to complete the crawling work and collect the real-time scene image. According to the obtained location by using the positioning auxiliary device, the position of the real-time detection image in a virtual 3-D model was calibrated. Through comparing of the real-time detection images and the computer simulation images, the defects or foreign matter fall into could be accurately positioning, so as to repair and clean up conveniently.

Automated interpretation of ventilation-perfusion lung scintigrams for the diagnosis of pulmonary embolism using artificial neural networks.

PubMed

Holst, H; Aström, K; Järund, A; Palmer, J; Heyden, A; Kahl, F; Tägil, K; Evander, E; Sparr, G; Edenbrandt, L

2000-04-01

The purpose of this study was to develop a completely automated method for the interpretation of ventilation-perfusion (V-P) lung scintigrams used in the diagnosis of pulmonary embolism. An artificial neural network was trained for the diagnosis of pulmonary embolism using 18 automatically obtained features from each set of V-P scintigrams. The techniques used to process the images included their alignment to templates, the construction of quotient images based on the ventilation and perfusion images, and the calculation of measures describing V-P mismatches in the quotient images. The templates represented lungs of normal size and shape without any pathological changes. Images that could not be properly aligned to the templates were detected and excluded automatically. After exclusion of those V-P scintigrams not properly aligned to the templates, 478 V-P scintigrams remained in a training group of consecutive patients with suspected pulmonary embolism, and a further 87 V-P scintigrams formed a separate test group comprising patients who had undergone pulmonary angiography. The performance of the neural network, measured as the area under the receiver operating characteristic curve, was 0.87 (95% confidence limits 0.82-0.92) in the training group and 0.79 (0.69-0.88) in the test group. It is concluded that a completely automated method can be used for the interpretation of V-P scintigrams. The performance of this method is similar to others previously presented, whereby features were extracted manually.

[Application of automatic photography in Schistosoma japonicum miracidium hatching experiments].

PubMed

Ming-Li, Zhou; Ai-Ling, Cai; Xue-Feng, Wang

2016-05-20

To explore the value of automatic photography in the observation of results of Schistosoma japonicum miracidium hatching experiments. Some fresh S. japonicum eggs were added into cow feces, and the samples of feces were divided into a low infested experimental group and a high infested group (40 samples each group). In addition, there was a negative control group with 40 samples of cow feces without S. japonicum eggs. The conventional nylon bag S. japonicum miracidium hatching experiments were performed. The process was observed with the method of flashlight and magnifying glass combined with automatic video (automatic photography method), and, at the same time, with the naked eye observation method. The results were compared. In the low infested group, the miracidium positive detection rates were 57.5% and 85.0% by the naked eye observation method and automatic photography method, respectively ( χ 2 = 11.723, P < 0.05). In the high infested group, the positive detection rates were 97.5% and 100% by the naked eye observation method and automatic photography method, respectively ( χ 2 = 1.253, P > 0.05). In the two infested groups, the average positive detection rates were 77.5% and 92.5% by the naked eye observation method and automatic photography method, respectively ( χ 2 = 6.894, P < 0.05). The automatic photography can effectively improve the positive detection rate in the S. japonicum miracidium hatching experiments.

Cross-terminology mapping challenges: a demonstration using medication terminological systems.

PubMed

Saitwal, Himali; Qing, David; Jones, Stephen; Bernstam, Elmer V; Chute, Christopher G; Johnson, Todd R

2012-08-01

Standardized terminological systems for biomedical information have provided considerable benefits to biomedical applications and research. However, practical use of this information often requires mapping across terminological systems-a complex and time-consuming process. This paper demonstrates the complexity and challenges of mapping across terminological systems in the context of medication information. It provides a review of medication terminological systems and their linkages, then describes a case study in which we mapped proprietary medication codes from an electronic health record to SNOMED CT and the UMLS Metathesaurus. The goal was to create a polyhierarchical classification system for querying an i2b2 clinical data warehouse. We found that three methods were required to accurately map the majority of actively prescribed medications. Only 62.5% of source medication codes could be mapped automatically. The remaining codes were mapped using a combination of semi-automated string comparison with expert selection, and a completely manual approach. Compound drugs were especially difficult to map: only 7.5% could be mapped using the automatic method. General challenges to mapping across terminological systems include (1) the availability of up-to-date information to assess the suitability of a given terminological system for a particular use case, and to assess the quality and completeness of cross-terminology links; (2) the difficulty of correctly using complex, rapidly evolving, modern terminologies; (3) the time and effort required to complete and evaluate the mapping; (4) the need to address differences in granularity between the source and target terminologies; and (5) the need to continuously update the mapping as terminological systems evolve. Copyright © 2012 Elsevier Inc. All rights reserved.

Cross-terminology mapping challenges: A demonstration using medication terminological systems

PubMed Central

Saitwal, Himali; Qing, David; Jones, Stephen; Bernstam, Elmer; Chute, Christopher G.; Johnson, Todd R.

2015-01-01

Standardized terminological systems for biomedical information have provided considerable benefits to biomedical applications and research. However, practical use of this information often requires mapping across terminological systems—a complex and time-consuming process. This paper demonstrates the complexity and challenges of mapping across terminological systems in the context of medication information. It provides a review of medication terminological systems and their linkages, then describes a case study in which we mapped proprietary medication codes from an electronic health record to SNOMED-CT and the UMLS Metathesaurus. The goal was to create a polyhierarchical classification system for querying an i2b2 clinical data warehouse. We found that three methods were required to accurately map the majority of actively prescribed medications. Only 62.5% of source medication codes could be mapped automatically. The remaining codes were mapped using a combination of semi-automated string comparison with expert selection, and a completely manual approach. Compound drugs were especially difficult to map: only 7.5% could be mapped using the automatic method. General challenges to mapping across terminological systems include (1) the availability of up-to-date information to assess the suitability of a given terminological system for a particular use case, and to assess the quality and completeness of cross-terminology links; (2) the difficulty of correctly using complex, rapidly evolving, modern terminologies; (3) the time and effort required to complete and evaluate the mapping; (4) the need to address differences in granularity between the source and target terminologies; and (5) the need to continuously update the mapping as terminological systems evolve. PMID:22750536

Compressible sleeve provides automatic centering for grinding or turning of cylinders

NASA Technical Reports Server (NTRS)

Rohrer, J. A.

1968-01-01

Elastomeric sleeve supported on a threaded mandrel automatically centers cylindrical castings for grinding or turning. By expanding the diameter of the sleeve with pressure against the ends, the casting becomes rigidly supported and the surfacing operation can be completed.

High-powered automatic latching device

NASA Technical Reports Server (NTRS)

Cobin, J. C.; Rhodes, L. L.

1970-01-01

Latches automatically lock together two remotely controlled bodies when their triggers are engaged by the docking ring of the lesser body. Latches are disengaged by manual actuation of the handle of each latch through two complete cycles. Emergency locking by manual actuation is also provided.

Designing and Implementing a Retrospective Earthquake Detection Framework at the U.S. Geological Survey National Earthquake Information Center

NASA Astrophysics Data System (ADS)

Patton, J.; Yeck, W.; Benz, H.

2017-12-01

The U.S. Geological Survey National Earthquake Information Center (USGS NEIC) is implementing and integrating new signal detection methods such as subspace correlation, continuous beamforming, multi-band picking and automatic phase identification into near-real-time monitoring operations. Leveraging the additional information from these techniques help the NEIC utilize a large and varied network on local to global scales. The NEIC is developing an ordered, rapid, robust, and decentralized framework for distributing seismic detection data as well as a set of formalized formatting standards. These frameworks and standards enable the NEIC to implement a seismic event detection framework that supports basic tasks, including automatic arrival time picking, social media based event detections, and automatic association of different seismic detection data into seismic earthquake events. In addition, this framework enables retrospective detection processing such as automated S-wave arrival time picking given a detected event, discrimination and classification of detected events by type, back-azimuth and slowness calculations, and ensuring aftershock and induced sequence detection completeness. These processes and infrastructure improve the NEIC's capabilities, accuracy, and speed of response. In addition, this same infrastructure provides an improved and convenient structure to support access to automatic detection data for both research and algorithmic development.

Reliable Analysis of Single-Unit Recordings from the Human Brain under Noisy Conditions: Tracking Neurons over Hours

PubMed Central

Boström, Jan; Elger, Christian E.; Mormann, Florian

2016-01-01

Recording extracellulary from neurons in the brains of animals in vivo is among the most established experimental techniques in neuroscience, and has recently become feasible in humans. Many interesting scientific questions can be addressed only when extracellular recordings last several hours, and when individual neurons are tracked throughout the entire recording. Such questions regard, for example, neuronal mechanisms of learning and memory consolidation, and the generation of epileptic seizures. Several difficulties have so far limited the use of extracellular multi-hour recordings in neuroscience: Datasets become huge, and data are necessarily noisy in clinical recording environments. No methods for spike sorting of such recordings have been available. Spike sorting refers to the process of identifying the contributions of several neurons to the signal recorded in one electrode. To overcome these difficulties, we developed Combinato: a complete data-analysis framework for spike sorting in noisy recordings lasting twelve hours or more. Our framework includes software for artifact rejection, automatic spike sorting, manual optimization, and efficient visualization of results. Our completely automatic framework excels at two tasks: It outperforms existing methods when tested on simulated and real data, and it enables researchers to analyze multi-hour recordings. We evaluated our methods on both short and multi-hour simulated datasets. To evaluate the performance of our methods in an actual neuroscientific experiment, we used data from from neurosurgical patients, recorded in order to identify visually responsive neurons in the medial temporal lobe. These neurons responded to the semantic content, rather than to visual features, of a given stimulus. To test our methods with multi-hour recordings, we made use of neurons in the human medial temporal lobe that respond selectively to the same stimulus in the evening and next morning. PMID:27930664

Development of Control System for Hydrolysis Crystallization Process

NASA Astrophysics Data System (ADS)

Wan, Feng; Shi, Xiao-Ming; Feng, Fang-Fang

2016-05-01

Sulfate method for producing titanium dioxide is commonly used in China, but the determination of crystallization time is artificially which leads to a big error and is harmful to the operators. In this paper a new method for determining crystallization time is proposed. The method adopts the red laser as the light source, uses the silicon photocell as reflection light receiving component, using optical fiber as the light transmission element, differential algorithm is adopted in the software to realize the determination of the crystallizing time. The experimental results show that the method can realize the determination of crystallization point automatically and accurately, can replace manual labor and protect the health of workers, can be applied to practice completely.

Automatic location of L/H transition times for physical studies with a large statistical basis

NASA Astrophysics Data System (ADS)

González, S.; Vega, J.; Murari, A.; Pereira, A.; Dormido-Canto, S.; Ramírez, J. M.; contributors, JET-EFDA

2012-06-01

Completely automatic techniques to estimate and validate L/H transition times can be essential in L/H transition analyses. The generation of databases with hundreds of transition times and without human intervention is an important step to accomplish (a) L/H transition physics analysis, (b) validation of L/H theoretical models and (c) creation of L/H scaling laws. An entirely unattended methodology is presented in this paper to build large databases of transition times in JET using time series. The proposed technique has been applied to a dataset of 551 JET discharges between campaigns C21 and C26. A prediction with discharges that show a clear signature in time series is made through the locating properties of the wavelet transform. It is an accurate prediction and the uncertainty interval is ±3.2 ms. The discharges with a non-clear pattern in the time series use an L/H mode classifier based on discharges with a clear signature. In this case, the estimation error shows a distribution with mean and standard deviation of 27.9 ms and 37.62 ms, respectively. Two different regression methods have been applied to the measurements acquired at the transition times identified by the automatic system. The obtained scaling laws for the threshold power are not significantly different from those obtained using the data at the transition times determined manually by the experts. The automatic methods allow performing physical studies with a large number of discharges, showing, for example, that there are statistically different types of transitions characterized by different scaling laws.

Real-time automatic registration in optical surgical navigation

NASA Astrophysics Data System (ADS)

Lin, Qinyong; Yang, Rongqian; Cai, Ken; Si, Xuan; Chen, Xiuwen; Wu, Xiaoming

2016-05-01

An image-guided surgical navigation system requires the improvement of the patient-to-image registration time to enhance the convenience of the registration procedure. A critical step in achieving this aim is performing a fully automatic patient-to-image registration. This study reports on a design of custom fiducial markers and the performance of a real-time automatic patient-to-image registration method using these markers on the basis of an optical tracking system for rigid anatomy. The custom fiducial markers are designed to be automatically localized in both patient and image spaces. An automatic localization method is performed by registering a point cloud sampled from the three dimensional (3D) pedestal model surface of a fiducial marker to each pedestal of fiducial markers searched in image space. A head phantom is constructed to estimate the performance of the real-time automatic registration method under four fiducial configurations. The head phantom experimental results demonstrate that the real-time automatic registration method is more convenient, rapid, and accurate than the manual method. The time required for each registration is approximately 0.1 s. The automatic localization method precisely localizes the fiducial markers in image space. The averaged target registration error for the four configurations is approximately 0.7 mm. The automatic registration performance is independent of the positions relative to the tracking system and the movement of the patient during the operation.

Automata learning algorithms and processes for providing more complete systems requirements specification by scenario generation, CSP-based syntax-oriented model construction, and R2D2C system requirements transformation

NASA Technical Reports Server (NTRS)

Margaria, Tiziana (Inventor); Hinchey, Michael G. (Inventor); Rouff, Christopher A. (Inventor); Rash, James L. (Inventor); Steffen, Bernard (Inventor)

2010-01-01

Systems, methods and apparatus are provided through which in some embodiments, automata learning algorithms and techniques are implemented to generate a more complete set of scenarios for requirements based programming. More specifically, a CSP-based, syntax-oriented model construction, which requires the support of a theorem prover, is complemented by model extrapolation, via automata learning. This may support the systematic completion of the requirements, the nature of the requirement being partial, which provides focus on the most prominent scenarios. This may generalize requirement skeletons by extrapolation and may indicate by way of automatically generated traces where the requirement specification is too loose and additional information is required.

ACIR: automatic cochlea image registration

NASA Astrophysics Data System (ADS)

Al-Dhamari, Ibraheem; Bauer, Sabine; Paulus, Dietrich; Lissek, Friedrich; Jacob, Roland

2017-02-01

Efficient Cochlear Implant (CI) surgery requires prior knowledge of the cochlea's size and its characteristics. This information helps to select suitable implants for different patients. To get these measurements, a segmentation method of cochlea medical images is needed. An important pre-processing step for good cochlea segmentation involves efficient image registration. The cochlea's small size and complex structure, in addition to the different resolutions and head positions during imaging, reveals a big challenge for the automated registration of the different image modalities. In this paper, an Automatic Cochlea Image Registration (ACIR) method for multi- modal human cochlea images is proposed. This method is based on using small areas that have clear structures from both input images instead of registering the complete image. It uses the Adaptive Stochastic Gradient Descent Optimizer (ASGD) and Mattes's Mutual Information metric (MMI) to estimate 3D rigid transform parameters. The use of state of the art medical image registration optimizers published over the last two years are studied and compared quantitatively using the standard Dice Similarity Coefficient (DSC). ACIR requires only 4.86 seconds on average to align cochlea images automatically and to put all the modalities in the same spatial locations without human interference. The source code is based on the tool elastix and is provided for free as a 3D Slicer plugin. Another contribution of this work is a proposed public cochlea standard dataset which can be downloaded for free from a public XNAT server.

LYRA, a webserver for lymphocyte receptor structural modeling.

PubMed

Klausen, Michael Schantz; Anderson, Mads Valdemar; Jespersen, Martin Closter; Nielsen, Morten; Marcatili, Paolo

2015-07-01

The accurate structural modeling of B- and T-cell receptors is fundamental to gain a detailed insight in the mechanisms underlying immunity and in developing new drugs and therapies. The LYRA (LYmphocyte Receptor Automated modeling) web server (http://www.cbs.dtu.dk/services/LYRA/) implements a complete and automated method for building of B- and T-cell receptor structural models starting from their amino acid sequence alone. The webserver is freely available and easy to use for non-specialists. Upon submission, LYRA automatically generates alignments using ad hoc profiles, predicts the structural class of each hypervariable loop, selects the best templates in an automatic fashion, and provides within minutes a complete 3D model that can be downloaded or inspected online. Experienced users can manually select or exclude template structures according to case specific information. LYRA is based on the canonical structure method, that in the last 30 years has been successfully used to generate antibody models of high accuracy, and in our benchmarks this approach proves to achieve similarly good results on TCR modeling, with a benchmarked average RMSD accuracy of 1.29 and 1.48 Å for B- and T-cell receptors, respectively. To the best of our knowledge, LYRA is the first automated server for the prediction of TCR structure. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Automatic thermographic image defect detection of composites

NASA Astrophysics Data System (ADS)

Luo, Bin; Liebenberg, Bjorn; Raymont, Jeff; Santospirito, SP

2011-05-01

Detecting defects, and especially reliably measuring defect sizes, are critical objectives in automatic NDT defect detection applications. In this work, the Sentence software is proposed for the analysis of pulsed thermography and near IR images of composite materials. Furthermore, the Sentence software delivers an end-to-end, user friendly platform for engineers to perform complete manual inspections, as well as tools that allow senior engineers to develop inspection templates and profiles, reducing the requisite thermographic skill level of the operating engineer. Finally, the Sentence software can also offer complete independence of operator decisions by the fully automated "Beep on Defect" detection functionality. The end-to-end automatic inspection system includes sub-systems for defining a panel profile, generating an inspection plan, controlling a robot-arm and capturing thermographic images to detect defects. A statistical model has been built to analyze the entire image, evaluate grey-scale ranges, import sentencing criteria and automatically detect impact damage defects. A full width half maximum algorithm has been used to quantify the flaw sizes. The identified defects are imported into the sentencing engine which then sentences (automatically compares analysis results against acceptance criteria) the inspection by comparing the most significant defect or group of defects against the inspection standards.

A New Approach for Mining Order-Preserving Submatrices Based on All Common Subsequences.

PubMed

Xue, Yun; Liao, Zhengling; Li, Meihang; Luo, Jie; Kuang, Qiuhua; Hu, Xiaohui; Li, Tiechen

2015-01-01

Order-preserving submatrices (OPSMs) have been applied in many fields, such as DNA microarray data analysis, automatic recommendation systems, and target marketing systems, as an important unsupervised learning model. Unfortunately, most existing methods are heuristic algorithms which are unable to reveal OPSMs entirely in NP-complete problem. In particular, deep OPSMs, corresponding to long patterns with few supporting sequences, incur explosive computational costs and are completely pruned by most popular methods. In this paper, we propose an exact method to discover all OPSMs based on frequent sequential pattern mining. First, an existing algorithm was adjusted to disclose all common subsequence (ACS) between every two row sequences, and therefore all deep OPSMs will not be missed. Then, an improved data structure for prefix tree was used to store and traverse ACS, and Apriori principle was employed to efficiently mine the frequent sequential pattern. Finally, experiments were implemented on gene and synthetic datasets. Results demonstrated the effectiveness and efficiency of this method.

Modeling and Representation of Human Hearts for Volumetric Measurement

PubMed Central

Guan, Qiu; Wang, Wanliang; Wu, Guang

2012-01-01

This paper investigates automatic construction of a three-dimensional heart model from a set of medical images, represents it in a deformable shape, and uses it to perform volumetric measurements. This not only significantly improves its reliability and accuracy but also makes it possible to derive valuable novel information, like various assessment and dynamic volumetric measurements. The method is based on a flexible model trained from hundreds of patient image sets by a genetic algorithm, which takes advantage of complete segmentation of the heart shape to form a geometrical heart model. For an image set of a new patient, an interpretation scheme is used to obtain its shape and evaluate some important parameters. Apart from automatic evaluation of traditional heart functions, some new information of cardiovascular diseases may be recognized from the volumetric analysis. PMID:22162723

HEPMath 1.4: A mathematica package for semi-automatic computations in high energy physics

NASA Astrophysics Data System (ADS)

Wiebusch, Martin

2015-10-01

This article introduces the Mathematica package HEPMath which provides a number of utilities and algorithms for High Energy Physics computations in Mathematica. Its functionality is similar to packages like FormCalc or FeynCalc, but it takes a more complete and extensible approach to implementing common High Energy Physics notations in the Mathematica language, in particular those related to tensors and index contractions. It also provides a more flexible method for the generation of numerical code which is based on new features for C code generation in Mathematica. In particular it can automatically generate Python extension modules which make the compiled functions callable from Python, thus eliminating the need to write any code in a low-level language like C or Fortran. It also contains seamless interfaces to LHAPDF, FeynArts, and LoopTools.

Towards the Real-Time Evaluation of Collaborative Activities: Integration of an Automatic Rater of Collaboration Quality in the Classroom from the Teacher's Perspective

ERIC Educational Resources Information Center

Chounta, Irene-Angelica; Avouris, Nikolaos

2016-01-01

This paper presents the integration of a real time evaluation method of collaboration quality in a monitoring application that supports teachers in class orchestration. The method is implemented as an automatic rater of collaboration quality and studied in a real time scenario of use. We argue that automatic and semi-automatic methods which…

An Automatic Procedure for Combining Digital Images and Laser Scanner Data

NASA Astrophysics Data System (ADS)

Moussa, W.; Abdel-Wahab, M.; Fritsch, D.

2012-07-01

Besides improving both the geometry and the visual quality of the model, the integration of close-range photogrammetry and terrestrial laser scanning techniques directs at filling gaps in laser scanner point clouds to avoid modeling errors, reconstructing more details in higher resolution and recovering simple structures with less geometric details. Thus, within this paper a flexible approach for the automatic combination of digital images and laser scanner data is presented. Our approach comprises two methods for data fusion. The first method starts by a marker-free registration of digital images based on a point-based environment model (PEM) of a scene which stores the 3D laser scanner point clouds associated with intensity and RGB values. The PEM allows the extraction of accurate control information for the direct computation of absolute camera orientations with redundant information by means of accurate space resection methods. In order to use the computed relations between the digital images and the laser scanner data, an extended Helmert (seven-parameter) transformation is introduced and its parameters are estimated. Precedent to that, in the second method, the local relative orientation parameters of the camera images are calculated by means of an optimized Structure and Motion (SaM) reconstruction method. Then, using the determined transformation parameters results in having absolute oriented images in relation to the laser scanner data. With the resulting absolute orientations we have employed robust dense image reconstruction algorithms to create oriented dense image point clouds, which are automatically combined with the laser scanner data to form a complete detailed representation of a scene. Examples of different data sets are shown and experimental results demonstrate the effectiveness of the presented procedures.

Automatic image enhancement based on multi-scale image decomposition

NASA Astrophysics Data System (ADS)

Feng, Lu; Wu, Zhuangzhi; Pei, Luo; Long, Xiong

2014-01-01

In image processing and computational photography, automatic image enhancement is one of the long-range objectives. Recently the automatic image enhancement methods not only take account of the globe semantics, like correct color hue and brightness imbalances, but also the local content of the image, such as human face and sky of landscape. In this paper we describe a new scheme for automatic image enhancement that considers both global semantics and local content of image. Our automatic image enhancement method employs the multi-scale edge-aware image decomposition approach to detect the underexposure regions and enhance the detail of the salient content. The experiment results demonstrate the effectiveness of our approach compared to existing automatic enhancement methods.

An Efficient Method for Automatic Road Extraction Based on Multiple Features from LiDAR Data

NASA Astrophysics Data System (ADS)

Li, Y.; Hu, X.; Guan, H.; Liu, P.

2016-06-01

The road extraction in urban areas is difficult task due to the complicated patterns and many contextual objects. LiDAR data directly provides three dimensional (3D) points with less occlusions and smaller shadows. The elevation information and surface roughness are distinguishing features to separate roads. However, LiDAR data has some disadvantages are not beneficial to object extraction, such as the irregular distribution of point clouds and lack of clear edges of roads. For these problems, this paper proposes an automatic road centerlines extraction method which has three major steps: (1) road center point detection based on multiple feature spatial clustering for separating road points from ground points, (2) local principal component analysis with least squares fitting for extracting the primitives of road centerlines, and (3) hierarchical grouping for connecting primitives into complete roads network. Compared with MTH (consist of Mean shift algorithm, Tensor voting, and Hough transform) proposed in our previous article, this method greatly reduced the computational cost. To evaluate the proposed method, the Vaihingen data set, a benchmark testing data provided by ISPRS for "Urban Classification and 3D Building Reconstruction" project, was selected. The experimental results show that our method achieve the same performance by less time in road extraction using LiDAR data.

10 CFR 431.134 - Uniform test methods for the measurement of energy consumption and water consumption of automatic...

Code of Federal Regulations, 2011 CFR

2011-01-01

... consumption and water consumption of automatic commercial ice makers. 431.134 Section 431.134 Energy... EQUIPMENT Automatic Commercial Ice Makers Test Procedures § 431.134 Uniform test methods for the measurement of energy consumption and water consumption of automatic commercial ice makers. (a) Scope. This...

Manual vs. automatic capture management in implantable cardioverter defibrillators and cardiac resynchronization therapy defibrillators.

PubMed

Murgatroyd, Francis D; Helmling, Erhard; Lemke, Bernd; Eber, Bernd; Mewis, Christian; van der Meer-Hensgens, Judith; Chang, Yanping; Khalameizer, Vladimir; Katz, Amos

2010-06-01

The Secura ICD and Consulta CRT-D are the first defibrillators to have automatic right atrial (RA), right ventricular (RV), and left ventricular (LV) capture management (CM). Complete CM was evaluated in an implantable cardioverter defibrillator (ICD) population. Two prospective clinical studies were conducted in 28 centres in Europe and Israel. Automatic CM data were compared with manual threshold measurements, the CM applicability was determined, and adjustments to pacing outputs were analysed. In total, 160 patients [age 64.6 +/- 10.4 years, 77% male, 80 ICD and 80 cardiac resynchronization therapy defibrillator (CRT-D)] were included. The differences between automatic and manual measurements were 2.5 V) due to raised RA threshold in seven (4.4%), high RV threshold in nine (5.6%), and high LV threshold in three patients (3.8%). All high threshold detections and all automatic modulations of pacing output were adjudicated appropriate. Complete CM adjusts pacing output appropriately, permitting a reduction in office visits while it may maximize device longevity. The study was registered at ClinicalTrials.gov identifiers: NCT00526227 and NCT00526162.

Comparison of liver volumetry on contrast-enhanced CT images: one semiautomatic and two automatic approaches.

PubMed

Cai, Wei; He, Baochun; Fan, Yingfang; Fang, Chihua; Jia, Fucang

2016-11-08

This study was to evaluate the accuracy, consistency, and efficiency of three liver volumetry methods- one interactive method, an in-house-developed 3D medical Image Analysis (3DMIA) system, one automatic active shape model (ASM)-based segmentation, and one automatic probabilistic atlas (PA)-guided segmentation method on clinical contrast-enhanced CT images. Forty-two datasets, including 27 normal liver and 15 space-occupying liver lesion patients, were retrospectively included in this study. The three methods - one semiautomatic 3DMIA, one automatic ASM-based, and one automatic PA-based liver volumetry - achieved an accuracy with VD (volume difference) of -1.69%, -2.75%, and 3.06% in the normal group, respectively, and with VD of -3.20%, -3.35%, and 4.14% in the space-occupying lesion group, respectively. However, the three methods achieved an efficiency of 27.63 mins, 1.26 mins, 1.18 mins on average, respectively, compared with the manual volumetry, which took 43.98 mins. The high intraclass correlation coefficient between the three methods and the manual method indicated an excel-lent agreement on liver volumetry. Significant differences in segmentation time were observed between the three methods (3DMIA, ASM, and PA) and the manual volumetry (p < 0.001), as well as between the automatic volumetries (ASM and PA) and the semiautomatic volumetry (3DMIA) (p < 0.001). The semiautomatic interactive 3DMIA, automatic ASM-based, and automatic PA-based liver volum-etry agreed well with manual gold standard in both the normal liver group and the space-occupying lesion group. The ASM- and PA-based automatic segmentation have better efficiency in clinical use. © 2016 The Authors.

Multi-atlas and label fusion approach for patient-specific MRI based skull estimation.

PubMed

Torrado-Carvajal, Angel; Herraiz, Joaquin L; Hernandez-Tamames, Juan A; San Jose-Estepar, Raul; Eryaman, Yigitcan; Rozenholc, Yves; Adalsteinsson, Elfar; Wald, Lawrence L; Malpica, Norberto

2016-04-01

MRI-based skull segmentation is a useful procedure for many imaging applications. This study describes a methodology for automatic segmentation of the complete skull from a single T1-weighted volume. The skull is estimated using a multi-atlas segmentation approach. Using a whole head computed tomography (CT) scan database, the skull in a new MRI volume is detected by nonrigid image registration of the volume to every CT, and combination of the individual segmentations by label-fusion. We have compared Majority Voting, Simultaneous Truth and Performance Level Estimation (STAPLE), Shape Based Averaging (SBA), and the Selective and Iterative Method for Performance Level Estimation (SIMPLE) algorithms. The pipeline has been evaluated quantitatively using images from the Retrospective Image Registration Evaluation database (reaching an overlap of 72.46 ± 6.99%), a clinical CT-MR dataset (maximum overlap of 78.31 ± 6.97%), and a whole head CT-MRI pair (maximum overlap 78.68%). A qualitative evaluation has also been performed on MRI acquisition of volunteers. It is possible to automatically segment the complete skull from MRI data using a multi-atlas and label fusion approach. This will allow the creation of complete MRI-based tissue models that can be used in electromagnetic dosimetry applications and attenuation correction in PET/MR. © 2015 Wiley Periodicals, Inc.

SigVox - A 3D feature matching algorithm for automatic street object recognition in mobile laser scanning point clouds

NASA Astrophysics Data System (ADS)

Wang, Jinhu; Lindenbergh, Roderik; Menenti, Massimo

2017-06-01

Urban road environments contain a variety of objects including different types of lamp poles and traffic signs. Its monitoring is traditionally conducted by visual inspection, which is time consuming and expensive. Mobile laser scanning (MLS) systems sample the road environment efficiently by acquiring large and accurate point clouds. This work proposes a methodology for urban road object recognition from MLS point clouds. The proposed method uses, for the first time, shape descriptors of complete objects to match repetitive objects in large point clouds. To do so, a novel 3D multi-scale shape descriptor is introduced, that is embedded in a workflow that efficiently and automatically identifies different types of lamp poles and traffic signs. The workflow starts by tiling the raw point clouds along the scanning trajectory and by identifying non-ground points. After voxelization of the non-ground points, connected voxels are clustered to form candidate objects. For automatic recognition of lamp poles and street signs, a 3D significant eigenvector based shape descriptor using voxels (SigVox) is introduced. The 3D SigVox descriptor is constructed by first subdividing the points with an octree into several levels. Next, significant eigenvectors of the points in each voxel are determined by principal component analysis (PCA) and mapped onto the appropriate triangle of a sphere approximating icosahedron. This step is repeated for different scales. By determining the similarity of 3D SigVox descriptors between candidate point clusters and training objects, street furniture is automatically identified. The feasibility and quality of the proposed method is verified on two point clouds obtained in opposite direction of a stretch of road of 4 km. 6 types of lamp pole and 4 types of road sign were selected as objects of interest. Ground truth validation showed that the overall accuracy of the ∼170 automatically recognized objects is approximately 95%. The results demonstrate that the proposed method is able to recognize street furniture in a practical scenario. Remaining difficult cases are touching objects, like a lamp pole close to a tree.

TU-D-209-05: Automatic Calculation of Organ and Effective Dose for CBCT and Interventional Fluoroscopic Procedures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiong, Z; Vijayan, S; Oines, A

Purpose: To compare PCXMC and EGSnrc calculated organ and effective radiation doses from cone-beam computed tomography (CBCT) and interventional fluoroscopically-guided procedures using automatic exposure-event grouping. Methods: For CBCT, we used PCXMC20Rotation.exe to automatically calculate the doses and compared the results to those calculated using EGSnrc with the Zubal patient phantom. For interventional procedures, we use the dose tracking system (DTS) which we previously developed to produce a log file of all geometry and exposure parameters for every x-ray pulse during a procedure, and the data in the log file is input into PCXMC and EGSnrc for dose calculation. A MATLABmore » program reads data from the log files and groups similar exposures to reduce calculation time. The definition files are then automatically generated in the format used by PCXMC and EGSnrc. Processing is done at the end of the procedure after all exposures are completed. Results: For the Toshiba Infinix CBCT LCI-Middle-Abdominal protocol, most organ doses calculated with PCXMC20Rotation closely matched those calculated with EGSnrc. The effective doses were 33.77 mSv with PCXMC20Rotation and 32.46 mSv with EGSnrc. For a simulated interventional cardiac procedure, similar close agreement in organ dose was obtained between the two codes; the effective doses were 12.02 mSv with PCXMC and 11.35 mSv with EGSnrc. The calculations can be completed on a PC without manual intervention in less than 15 minutes with PCXMC and in about 10 hours with EGSnrc, depending on the level of data grouping and accuracy desired. Conclusion: Effective dose and most organ doses in CBCT and interventional radiology calculated by PCXMC closely match those calculated by EGSnrc. Data grouping, which can be done automatically, makes the calculation time with PCXMC on a standard PC acceptable. This capability expands the dose information that can be provided by the DTS. Partial support from NIH Grant R01-EB002873 and Toshiba Medical Systems Corp.« less

Automatic multiresolution age-related macular degeneration detection from fundus images

NASA Astrophysics Data System (ADS)

Garnier, Mickaël.; Hurtut, Thomas; Ben Tahar, Houssem; Cheriet, Farida

2014-03-01

Age-related Macular Degeneration (AMD) is a leading cause of legal blindness. As the disease progress, visual loss occurs rapidly, therefore early diagnosis is required for timely treatment. Automatic, fast and robust screening of this widespread disease should allow an early detection. Most of the automatic diagnosis methods in the literature are based on a complex segmentation of the drusen, targeting a specific symptom of the disease. In this paper, we present a preliminary study for AMD detection from color fundus photographs using a multiresolution texture analysis. We analyze the texture at several scales by using a wavelet decomposition in order to identify all the relevant texture patterns. Textural information is captured using both the sign and magnitude components of the completed model of Local Binary Patterns. An image is finally described with the textural pattern distributions of the wavelet coefficient images obtained at each level of decomposition. We use a Linear Discriminant Analysis for feature dimension reduction, to avoid the curse of dimensionality problem, and image classification. Experiments were conducted on a dataset containing 45 images (23 healthy and 22 diseased) of variable quality and captured by different cameras. Our method achieved a recognition rate of 93:3%, with a specificity of 95:5% and a sensitivity of 91:3%. This approach shows promising results at low costs that in agreement with medical experts as well as robustness to both image quality and fundus camera model.

Automatic characterization of neointimal tissue by intravascular optical coherence tomography.

PubMed

Ughi, Giovanni J; Steigerwald, Kristin; Adriaenssens, Tom; Desmet, Walter; Guagliumi, Giulio; Joner, Michael; D'hooge, Jan

2014-02-01

Intravascular optical coherence tomography (IVOCT) is rapidly becoming the method of choice for assessing vessel healing after stent implantation due to its unique axial resolution <20  μm. The amount of neointimal coverage is an important parameter. In addition, the characterization of neointimal tissue maturity is also of importance for an accurate analysis, especially in the case of drug-eluting and bioresorbable stent devices. Previous studies indicated that well-organized mature neointimal tissue appears as a high-intensity, smooth, and homogeneous region in IVOCT images, while lower-intensity signal areas might correspond to immature tissue mainly composed of acellular material. A new method for automatic neointimal tissue characterization, based on statistical texture analysis and a supervised classification technique, is presented. Algorithm training and validation were obtained through the use of 53 IVOCT images supported by histology data from atherosclerotic New Zealand White rabbits. A pixel-wise classification accuracy of 87% and a two-dimensional region-based analysis accuracy of 92% (with sensitivity and specificity of 91% and 93%, respectively) were found, suggesting that a reliable automatic characterization of neointimal tissue was achieved. This may potentially expand the clinical value of IVOCT in assessing the completeness of stent healing and speed up the current analysis methodologies (which are, due to their time- and energy-consuming character, not suitable for application in large clinical trials and clinical practice), potentially allowing for a wider use of IVOCT technology.

Representation and Reconconstruction of Triangular Irregular Networks with Vertical Walls

NASA Astrophysics Data System (ADS)

Gorte, B.; Lesparre, J.

2012-06-01

Point clouds obtained by aerial laser scanning are a convenient input source for high resolution 2.5d elevation models, such as the Dutch AHN-2. More challenging is the fully automatic reconstruction of 3d city models. An actual demand for a combined 2.5d terrain and 3d city model for an urban hydrology application led to the design of an extension to the well-known Delaunay triangulated irregular networks (TINs) as to accommodate vertical walls. In addition we introduce methods to generate and refine models adhering to our data structure. These are based on combining two approaches: a representation of the TIN using stars of vertices and triangles, together with segmenting the TIN on the basis of coplanarity of adjacent triangles. The approach is supposed to deliver the complete model including walls at the correct locations, without relying on additional map data, as these often lack completeness, actuality and accuracy, and moreover most of the time do not account for parts facades not going down to street level. However, automatic detection of height discontinuities to obtain the exact location of the walls is currently still under implementation.

10 CFR 431.134 - Uniform test methods for the measurement of energy and water consumption of automatic commercial...

Code of Federal Regulations, 2013 CFR

2013-01-01

... water consumption of automatic commercial ice makers. 431.134 Section 431.134 Energy DEPARTMENT OF... Automatic Commercial Ice Makers Test Procedures § 431.134 Uniform test methods for the measurement of energy and water consumption of automatic commercial ice makers. (a) Scope. This section provides the test...

10 CFR 431.134 - Uniform test methods for the measurement of energy and water consumption of automatic commercial...

Code of Federal Regulations, 2014 CFR

2014-01-01

... water consumption of automatic commercial ice makers. 431.134 Section 431.134 Energy DEPARTMENT OF... Automatic Commercial Ice Makers Test Procedures § 431.134 Uniform test methods for the measurement of energy and water consumption of automatic commercial ice makers. (a) Scope. This section provides the test...

a Low-Cost and Portable System for 3d Reconstruction of Texture-Less Objects

NASA Astrophysics Data System (ADS)

Hosseininaveh, A.; Yazdan, R.; Karami, A.; Moradi, M.; Ghorbani, F.

2015-12-01

The optical methods for 3D modelling of objects can be classified into two categories including image-based and range-based methods. Structure from Motion is one of the image-based methods implemented in commercial software. In this paper, a low-cost and portable system for 3D modelling of texture-less objects is proposed. This system includes a rotating table designed and developed by using a stepper motor and a very light rotation plate. The system also has eight laser light sources with very dense and strong beams which provide a relatively appropriate pattern on texture-less objects. In this system, regarding to the step of stepper motor, images are semi automatically taken by a camera. The images can be used in structure from motion procedures implemented in Agisoft software.To evaluate the performance of the system, two dark objects were used. The point clouds of these objects were obtained by spraying a light powders on the objects and exploiting a GOM laser scanner. Then these objects were placed on the proposed turntable. Several convergent images were taken from each object while the laser light sources were projecting the pattern on the objects. Afterward, the images were imported in VisualSFM as a fully automatic software package for generating an accurate and complete point cloud. Finally, the obtained point clouds were compared to the point clouds generated by the GOM laser scanner. The results showed the ability of the proposed system to produce a complete 3D model from texture-less objects.

Automated single-slide staining device. [in clinical bacteriology

NASA Technical Reports Server (NTRS)

Wilkins, J. R.; Mills, S. M.

1975-01-01

An automatic single-slide Gram staining device is described. A timer-actuated solenoid controls the dispensing of gentian violet, Gram iodine solution, decolorizer, and 1% aqueous safranin in proper sequence and for the time required for optimum staining. The amount of stain or reagent delivered is controlled by means of stopcocks below each solenoid. Used stains and reagents can be flushed automatically or manually. Smears Gram stained automatically are equal in quality to those prepared manually. The time to complete one Gram cycle is 4.80 min.

Small passenger car transmission test: Mercury Lynx ATX transmission

NASA Technical Reports Server (NTRS)

Bujold, M. P.

1981-01-01

The testing of a Mercury Lynx automatic transmission is reported. The transmission was tested in accordance with a passenger car automatic transmission test code (SAE J65lb) which required drive performance, coast performance, and no load test conditions. Under these conditions, the transmission attained maximum efficiencies in the mid-ninety percent range both for drive performance test and coast performance tests. The torque, speed, and efficiency curves are presented, which provide the complete performance characteristics for the Mercury Lynx automatic transmission.

Automatic segmentation of amyloid plaques in MR images using unsupervised SVM

PubMed Central

Iordanescu, Gheorghe; Venkatasubramanian, Palamadai N.; Wyrwicz, Alice M.

2011-01-01

Deposition of the β-amyloid peptide (Aβ) is an important pathological hallmark of Alzheimer’s disease (AD). However, reliable quantification of amyloid plaques in both human and animal brains remains a challenge. We present here a novel automatic plaque segmentation algorithm based on the intrinsic MR signal characteristics of plaques. This algorithm identifies plaque candidates in MR data by using watershed transform, which extracts regions with low intensities completely surrounded by higher intensity neighbors. These candidates are classified as plaque or non-plaque by an unsupervised learning method using features derived from the MR data intensity. The algorithm performance is validated by comparison with histology. We also demonstrate the algorithm’s ability to detect age-related changes in plaque load ex vivo in 5×FAD APP transgenic mice. To our knowledge, this work represents the first quantitative method for characterizing amyloid plaques in MRI data. The proposed method can be used to describe the spatio-temporal progression of amyloid deposition, which is necessary for understanding the evolution of plaque pathology in mouse models of AD and to evaluate the efficacy of emergent amyloid-targeting therapies in preclinical trials. PMID:22189675

Research and Development of Fully Automatic Alien Smoke Stack and Packaging System

NASA Astrophysics Data System (ADS)

Yang, Xudong; Ge, Qingkuan; Peng, Tao; Zuo, Ping; Dong, Weifu

2017-12-01

The problem of low efficiency of manual sorting packaging for the current tobacco distribution center, which developed a set of safe efficient and automatic type of alien smoke stack and packaging system. The functions of fully automatic alien smoke stack and packaging system adopt PLC control technology, servo control technology, robot technology, image recognition technology and human-computer interaction technology. The characteristics, principles, control process and key technology of the system are discussed in detail. Through the installation and commissioning fully automatic alien smoke stack and packaging system has a good performance and has completed the requirements for shaped cigarette.

Automatic inoculating apparatus. [includes movable carraige, drive motor, and swabbing motor

NASA Technical Reports Server (NTRS)

Wilkins, J. R.; Mills, S. M. (Inventor)

1974-01-01

An automatic inoculating apparatus for agar trays is described and using a simple inoculating element, such as a cotton swab or inoculating loop. The apparatus includes a movable carriage for supporting the tray to be inoculated, a drive motor for moving the tray along a trackway, and a swabbing motor for automatically swabbing the tray during the movement. An actuator motor controls lowering of the inoculating element onto the tray and lifting of the inoculating element. An electrical control system, including limit microswitches, enables automatic control of the actuator motor and return of the carriage to the initial position after inoculating is completed.

Automatic Operation For A Robot Lawn Mower

NASA Astrophysics Data System (ADS)

Huang, Y. Y.; Cao, Z. L.; Oh, S. J.; Kattan, E. U.; Hall, E. L.

1987-02-01

A domestic mobile robot, lawn mower, which performs the automatic operation mode, has been built up in the Center of Robotics Research, University of Cincinnati. The robot lawn mower automatically completes its work with the region filling operation, a new kind of path planning for mobile robots. Some strategies for region filling of path planning have been developed for a partly-known or a unknown environment. Also, an advanced omnidirectional navigation system and a multisensor-based control system are used in the automatic operation. Research on the robot lawn mower, especially on the region filling of path planning, is significant in industrial and agricultural applications.

Comparison of liver volumetry on contrast‐enhanced CT images: one semiautomatic and two automatic approaches

PubMed Central

Cai, Wei; He, Baochun; Fang, Chihua

2016-01-01

This study was to evaluate the accuracy, consistency, and efficiency of three liver volumetry methods— one interactive method, an in‐house‐developed 3D medical Image Analysis (3DMIA) system, one automatic active shape model (ASM)‐based segmentation, and one automatic probabilistic atlas (PA)‐guided segmentation method on clinical contrast‐enhanced CT images. Forty‐two datasets, including 27 normal liver and 15 space‐occupying liver lesion patients, were retrospectively included in this study. The three methods — one semiautomatic 3DMIA, one automatic ASM‐based, and one automatic PA‐based liver volumetry — achieved an accuracy with VD (volume difference) of −1.69%,−2.75%, and 3.06% in the normal group, respectively, and with VD of −3.20%,−3.35%, and 4.14% in the space‐occupying lesion group, respectively. However, the three methods achieved an efficiency of 27.63 mins, 1.26 mins, 1.18 mins on average, respectively, compared with the manual volumetry, which took 43.98 mins. The high intraclass correlation coefficient between the three methods and the manual method indicated an excellent agreement on liver volumetry. Significant differences in segmentation time were observed between the three methods (3DMIA, ASM, and PA) and the manual volumetry (p<0.001), as well as between the automatic volumetries (ASM and PA) and the semiautomatic volumetry (3DMIA) (p<0.001). The semiautomatic interactive 3DMIA, automatic ASM‐based, and automatic PA‐based liver volumetry agreed well with manual gold standard in both the normal liver group and the space‐occupying lesion group. The ASM‐ and PA‐based automatic segmentation have better efficiency in clinical use. PACS number(s): 87.55.‐x PMID:27929487

Tri-Clustered Tensor Completion for Social-Aware Image Tag Refinement.

PubMed

Tang, Jinhui; Shu, Xiangbo; Qi, Guo-Jun; Li, Zechao; Wang, Meng; Yan, Shuicheng; Jain, Ramesh

2017-08-01

Social image tag refinement, which aims to improve tag quality by automatically completing the missing tags and rectifying the noise-corrupted ones, is an essential component for social image search. Conventional approaches mainly focus on exploring the visual and tag information, without considering the user information, which often reveals important hints on the (in)correct tags of social images. Towards this end, we propose a novel tri-clustered tensor completion framework to collaboratively explore these three kinds of information to improve the performance of social image tag refinement. Specifically, the inter-relations among users, images and tags are modeled by a tensor, and the intra-relations between users, images and tags are explored by three regularizations respectively. To address the challenges of the super-sparse and large-scale tensor factorization that demands expensive computing and memory cost, we propose a novel tri-clustering method to divide the tensor into a certain number of sub-tensors by simultaneously clustering users, images and tags into a bunch of tri-clusters. And then we investigate two strategies to complete these sub-tensors by considering (in)dependence between the sub-tensors. Experimental results on a real-world social image database demonstrate the superiority of the proposed method compared with the state-of-the-art methods.

SCAMP: Automatic Astrometric and Photometric Calibration

NASA Astrophysics Data System (ADS)

Bertin, Emmanuel

2010-10-01

Astrometric and photometric calibrations have remained the most tiresome step in the reduction of large imaging surveys. SCAMP has been written to address this problem. The program efficiently computes accurate astrometric and photometric solutions for any arbitrary sequence of FITS images in a completely automatic way. SCAMP is released under the GNU General Public License.

A semi-automatic annotation tool for cooking video

NASA Astrophysics Data System (ADS)

Bianco, Simone; Ciocca, Gianluigi; Napoletano, Paolo; Schettini, Raimondo; Margherita, Roberto; Marini, Gianluca; Gianforme, Giorgio; Pantaleo, Giuseppe

2013-03-01

In order to create a cooking assistant application to guide the users in the preparation of the dishes relevant to their profile diets and food preferences, it is necessary to accurately annotate the video recipes, identifying and tracking the foods of the cook. These videos present particular annotation challenges such as frequent occlusions, food appearance changes, etc. Manually annotate the videos is a time-consuming, tedious and error-prone task. Fully automatic tools that integrate computer vision algorithms to extract and identify the elements of interest are not error free, and false positive and false negative detections need to be corrected in a post-processing stage. We present an interactive, semi-automatic tool for the annotation of cooking videos that integrates computer vision techniques under the supervision of the user. The annotation accuracy is increased with respect to completely automatic tools and the human effort is reduced with respect to completely manual ones. The performance and usability of the proposed tool are evaluated on the basis of the time and effort required to annotate the same video sequences.

Comparison of automatical thoughts among generalized anxiety disorder, major depressive disorder and generalized social phobia patients.

PubMed

Gül, A I; Simsek, G; Karaaslan, Ö; Inanir, S

2015-08-01

Automatic thoughts are measurable cognitive markers of the psychopathology and coping styles of individuals. This study measured and compared the automatic thoughts of patients with generalized anxiety disorder (GAD), major depressive disorder (MDD), and generalized social phobia (GSP). Fifty-two patients with GAD, 53 with MDD, and 50 with GSP and 52 healthy controls completed the validated Automatic Thoughts Questionnaire (ATQ) and a structured psychiatric interview. Patients with GAD, MDD, and GSP also completed the validated Generalized Anxiety Disorder-7 questionnaire, the Beck Depression Inventory (BDI), and the Liebowitz Social Anxiety Scale (LSAS) to determine the severity of their illnesses. All scales were completed before treatment and after diagnosis. The ATQ scores of all pairs of groups were compared. The ATQ scores of the GAD, MDD, and GSP groups were significantly higher than were those of the control group. We also found significant correlations among scores on the GAD-7, BDI, and LSAS. The mean age of patients with GSP was lower than was that of the other groups (30.90 ± 8.35). The significantly higher ATQ scores of the MDD, GAD, and GSP groups, compared with the control group, underscore the common cognitive psychopathology characterizing these three disorders. This finding confirms that similar cognitive therapy approaches should be effective for these patients. This study is the first to compare GAD, MDD, and GSP from a cognitive perspective.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jackson, K.A.; Neuman, M.C.; Simmonds, D.D.

An effective method for detecting computer misuse is the automatic monitoring and analysis of on-line user activity. This activity is reflected in the system audit record, in the system vulnerability posture, and in other evidence found through active testing of the system. During the last several years we have implemented an automatic misuse detection system at Los Alamos. This is the Network Anomaly Detection and Intrusion Reporter (NADIR). We are currently expanding NADIR to include processing of the Cray UNICOS operating system. This new component is called the UNICOS Realtime NADIR, or UNICORN. UNICORN summarizes user activity and system configurationmore » in statistical profiles. It compares these profiles to expert rules that define security policy and improper or suspicious behavior. It reports suspicious behavior to security auditors and provides tools to aid in follow-up investigations. The first phase of UNICORN development is nearing completion, and will be operational in late 1994.« less

An evaluation of automatic coronary artery calcium scoring methods with cardiac CT using the orCaScore framework.

PubMed

Wolterink, Jelmer M; Leiner, Tim; de Vos, Bob D; Coatrieux, Jean-Louis; Kelm, B Michael; Kondo, Satoshi; Salgado, Rodrigo A; Shahzad, Rahil; Shu, Huazhong; Snoeren, Miranda; Takx, Richard A P; van Vliet, Lucas J; van Walsum, Theo; Willems, Tineke P; Yang, Guanyu; Zheng, Yefeng; Viergever, Max A; Išgum, Ivana

2016-05-01

The amount of coronary artery calcification (CAC) is a strong and independent predictor of cardiovascular disease (CVD) events. In clinical practice, CAC is manually identified and automatically quantified in cardiac CT using commercially available software. This is a tedious and time-consuming process in large-scale studies. Therefore, a number of automatic methods that require no interaction and semiautomatic methods that require very limited interaction for the identification of CAC in cardiac CT have been proposed. Thus far, a comparison of their performance has been lacking. The objective of this study was to perform an independent evaluation of (semi)automatic methods for CAC scoring in cardiac CT using a publicly available standardized framework. Cardiac CT exams of 72 patients distributed over four CVD risk categories were provided for (semi)automatic CAC scoring. Each exam consisted of a noncontrast-enhanced calcium scoring CT (CSCT) and a corresponding coronary CT angiography (CCTA) scan. The exams were acquired in four different hospitals using state-of-the-art equipment from four major CT scanner vendors. The data were divided into 32 training exams and 40 test exams. A reference standard for CAC in CSCT was defined by consensus of two experts following a clinical protocol. The framework organizers evaluated the performance of (semi)automatic methods on test CSCT scans, per lesion, artery, and patient. Five (semi)automatic methods were evaluated. Four methods used both CSCT and CCTA to identify CAC, and one method used only CSCT. The evaluated methods correctly detected between 52% and 94% of CAC lesions with positive predictive values between 65% and 96%. Lesions in distal coronary arteries were most commonly missed and aortic calcifications close to the coronary ostia were the most common false positive errors. The majority (between 88% and 98%) of correctly identified CAC lesions were assigned to the correct artery. Linearly weighted Cohen's kappa for patient CVD risk categorization by the evaluated methods ranged from 0.80 to 1.00. A publicly available standardized framework for the evaluation of (semi)automatic methods for CAC identification in cardiac CT is described. An evaluation of five (semi)automatic methods within this framework shows that automatic per patient CVD risk categorization is feasible. CAC lesions at ambiguous locations such as the coronary ostia remain challenging, but their detection had limited impact on CVD risk determination.

[Development of a Computer-aided Diagnosis System to Distinguish between Benign and Malignant Mammary Tumors in Dynamic Magnetic Resonance Images: Automatic Detection of the Position with the Strongest Washout Effect in the Tumor].

PubMed

Miyazaki, Yoshiaki; Tabata, Nobuyuki; Taroura, Tomomi; Shinozaki, Kenji; Kubo, Yuichiro; Tokunaga, Eriko; Taguchi, Kenichi

We propose a computer-aided diagnostic (CAD) system that uses time-intensity curves to distinguish between benign and malignant mammary tumors. Many malignant tumors show a washout pattern in time-intensity curves. Therefore, we designed a program that automatically detects the position with the strongest washout effect using the technique, such as the subtraction technique, which extracts only the washout area in the tumor, and by scanning data in 2×2 pixel region of interest (ROI). Operation of this independently developed program was verified using a phantom system that simulated tumors. In three cases of malignant tumors, the washout pattern detection rate in images with manually set ROI was ≤6%, whereas the detection rate with our novel method was 100%. In one case of a benign tumor, when the same method was used, we checked that there was no washout effect and detected the persistent pattern. Thus, the distinction between benign and malignant tumors using our method was completely consistent with the pathological diagnoses made. Our novel method is therefore effective for differentiating between benign and malignant mammary tumors in dynamic magnetic resonance images.

Don't forget the lyrics! Spatiotemporal dynamics of neural mechanisms spontaneously evoked by gaps of silence in familiar and newly learned songs.

PubMed

Gabriel, Damien; Wong, Thian Chiew; Nicolier, Magali; Giustiniani, Julie; Mignot, Coralie; Noiret, Nicolas; Monnin, Julie; Magnin, Eloi; Pazart, Lionel; Moulin, Thierry; Haffen, Emmanuel; Vandel, Pierre

2016-07-01

The vast majority of people experience musical imagery, the sensation of reliving a song in absence of any external stimulation. Internal perception of a song can be deliberate and effortful, but also may occur involuntarily and spontaneously. Moreover, musical imagery is also involuntarily used for automatically completing missing parts of music or lyrics from a familiar song. The aim of our study was to explore the onset of musical imagery dynamics that leads to the automatic completion of missing lyrics. High-density electroencephalography was used to record the cerebral activity of twenty healthy volunteers while they were passively listening to unfamiliar songs, very familiar songs, and songs previously listened to for two weeks. Silent gaps inserted into these songs elicited a series of neural activations encompassing perceptual, attentional and cognitive mechanisms (range 100-500ms). Familiarity and learning effects emerged as early as 100ms and lasted 400ms after silence occurred. Although participants reported more easily mentally imagining lyrics in familiar rather than passively learnt songs, the onset of neural mechanisms and the power spectrum underlying musical imagery were similar for both types of songs. This study offers new insights into the musical imagery dynamics evoked by gaps of silence and on the role of familiarity and learning processes in the generation of these dynamics. The automatic and effortless method presented here is a potentially useful tool to understand failure in the familiarity and learning processes of pathological populations. Copyright © 2016 Elsevier Inc. All rights reserved.

MO-F-CAMPUS-I-01: A System for Automatically Calculating Organ and Effective Dose for Fluoroscopically-Guided Procedures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiong, Z; Vijayan, S; Rana, V

2015-06-15

Purpose: A system was developed that automatically calculates the organ and effective dose for individual fluoroscopically-guided procedures using a log of the clinical exposure parameters. Methods: We have previously developed a dose tracking system (DTS) to provide a real-time color-coded 3D- mapping of skin dose. This software produces a log file of all geometry and exposure parameters for every x-ray pulse during a procedure. The data in the log files is input into PCXMC, a Monte Carlo program that calculates organ and effective dose for projections and exposure parameters set by the user. We developed a MATLAB program to readmore » data from the log files produced by the DTS and to automatically generate the definition files in the format used by PCXMC. The processing is done at the end of a procedure after all exposures are completed. Since there are thousands of exposure pulses with various parameters for fluoroscopy, DA and DSA and at various projections, the data for exposures with similar parameters is grouped prior to entry into PCXMC to reduce the number of Monte Carlo calculations that need to be performed. Results: The software developed automatically transfers data from the DTS log file to PCXMC and runs the program for each grouping of exposure pulses. When the dose from all exposure events are calculated, the doses for each organ and all effective doses are summed to obtain procedure totals. For a complicated interventional procedure, the calculations can be completed on a PC without manual intervention in less than 30 minutes depending on the level of data grouping. Conclusion: This system allows organ dose to be calculated for individual procedures for every patient without tedious calculations or data entry so that estimates of stochastic risk can be obtained in addition to the deterministic risk estimate provided by the DTS. Partial support from NIH grant R01EB002873 and Toshiba Medical Systems Corp.« less

Automated matching of corresponding seed images of three simulator radiographs to allow 3D triangulation of implanted seeds.

PubMed

Altschuler, M D; Kassaee, A

1997-02-01

To match corresponding seed images in different radiographs so that the 3D seed locations can be triangulated automatically and without ambiguity requires (at least) three radiographs taken from different perspectives, and an algorithm that finds the proper permutations of the seed-image indices. Matching corresponding images in only two radiographs introduces inherent ambiguities which can be resolved only with the use of non-positional information obtained with intensive human effort. Matching images in three or more radiographs is an 'NP (Non-determinant in Polynomial time)-complete' problem. Although the matching problem is fundamental, current methods for three-radiograph seed-image matching use 'local' (seed-by-seed) methods that may lead to incorrect matchings. We describe a permutation-sampling method which not only gives good 'global' (full permutation) matches for the NP-complete three-radiograph seed-matching problem, but also determines the reliability of the radiographic data themselves, namely, whether the patient moved in the interval between radiographic perspectives.

Automated matching of corresponding seed images of three simulator radiographs to allow 3D triangulation of implanted seeds

NASA Astrophysics Data System (ADS)

Altschuler, Martin D.; Kassaee, Alireza

1997-02-01

To match corresponding seed images in different radiographs so that the 3D seed locations can be triangulated automatically and without ambiguity requires (at least) three radiographs taken from different perspectives, and an algorithm that finds the proper permutations of the seed-image indices. Matching corresponding images in only two radiographs introduces inherent ambiguities which can be resolved only with the use of non-positional information obtained with intensive human effort. Matching images in three or more radiographs is an `NP (Non-determinant in Polynomial time)-complete' problem. Although the matching problem is fundamental, current methods for three-radiograph seed-image matching use `local' (seed-by-seed) methods that may lead to incorrect matchings. We describe a permutation-sampling method which not only gives good `global' (full permutation) matches for the NP-complete three-radiograph seed-matching problem, but also determines the reliability of the radiographic data themselves, namely, whether the patient moved in the interval between radiographic perspectives.

Estimation of missing values in solar radiation data using piecewise interpolation methods: Case study at Penang city

NASA Astrophysics Data System (ADS)

Zainudin, Mohd Lutfi; Saaban, Azizan; Bakar, Mohd Nazari Abu

2015-12-01

The solar radiation values have been composed by automatic weather station using the device that namely pyranometer. The device is functions to records all the radiation values that have been dispersed, and these data are very useful for it experimental works and solar device's development. In addition, for modeling and designing on solar radiation system application is needed for complete data observation. Unfortunately, lack for obtained the complete solar radiation data frequently occur due to several technical problems, which mainly contributed by monitoring device. Into encountering this matter, estimation missing values in an effort to substitute absent values with imputed data. This paper aimed to evaluate several piecewise interpolation techniques likes linear, splines, cubic, and nearest neighbor into dealing missing values in hourly solar radiation data. Then, proposed an extendable work into investigating the potential used of cubic Bezier technique and cubic Said-ball method as estimator tools. As result, methods for cubic Bezier and Said-ball perform the best compare to another piecewise imputation technique.

Intra-operative adjustment of standard planes in C-arm CT image data.

PubMed

Brehler, Michael; Görres, Joseph; Franke, Jochen; Barth, Karl; Vetter, Sven Y; Grützner, Paul A; Meinzer, Hans-Peter; Wolf, Ivo; Nabers, Diana

2016-03-01

With the help of an intra-operative mobile C-arm CT, medical interventions can be verified and corrected, avoiding the need for a post-operative CT and a second intervention. An exact adjustment of standard plane positions is necessary for the best possible assessment of the anatomical regions of interest but the mobility of the C-arm causes the need for a time-consuming manual adjustment. In this article, we present an automatic plane adjustment at the example of calcaneal fractures. We developed two feature detection methods (2D and pseudo-3D) based on SURF key points and also transferred the SURF approach to 3D. Combined with an atlas-based registration, our algorithm adjusts the standard planes of the calcaneal C-arm images automatically. The robustness of the algorithms is evaluated using a clinical data set. Additionally, we tested the algorithm's performance for two registration approaches, two resolutions of C-arm images and two methods for metal artifact reduction. For the feature extraction, the novel 3D-SURF approach performs best. As expected, a higher resolution ([Formula: see text] voxel) leads also to more robust feature points and is therefore slightly better than the [Formula: see text] voxel images (standard setting of device). Our comparison of two different artifact reduction methods and the complete removal of metal in the images shows that our approach is highly robust against artifacts and the number and position of metal implants. By introducing our fast algorithmic processing pipeline, we developed the first steps for a fully automatic assistance system for the assessment of C-arm CT images.

WELDING METHOD

DOEpatents

Cornell, A.A.; Dunbar, J.V.; Ruffner, J.H.

1959-09-29

A semi-automatic method is described for the weld joining of pipes and fittings which utilizes the inert gasshielded consumable electrode electric arc welding technique, comprising laying down the root pass at a first peripheral velocity and thereafter laying down the filler passes over the root pass necessary to complete the weld by revolving the pipes and fittings at a second peripheral velocity different from the first peripheral velocity, maintaining the welding head in a fixed position as to the specific direction of revolution, while the longitudinal axis of the welding head is disposed angularly in the direction of revolution at amounts between twenty minutas and about four degrees from the first position.

[DNA extraction from bones and teeth using AutoMate Express forensic DNA extraction system].

PubMed

Gao, Lin-Lin; Xu, Nian-Lai; Xie, Wei; Ding, Shao-Cheng; Wang, Dong-Jing; Ma, Li-Qin; Li, You-Ying

2013-04-01

To explore a new method in order to extract DNA from bones and teeth automatically. Samples of 33 bones and 15 teeth were acquired by freeze-mill method and manual method, respectively. DNA materials were extracted and quantified from the triturated samples by AutoMate Express forensic DNA extraction system. DNA extraction from bones and teeth were completed in 3 hours using the AutoMate Express forensic DNA extraction system. There was no statistical difference between the two methods in the DNA concentration of bones. Both bones and teeth got the good STR typing by freeze-mill method, and the DNA concentration of teeth was higher than those by manual method. AutoMate Express forensic DNA extraction system is a new method to extract DNA from bones and teeth, which can be applied in forensic practice.

Automatic Query Formulations in Information Retrieval.

ERIC Educational Resources Information Center

Salton, G.; And Others

1983-01-01

Introduces methods designed to reduce role of search intermediaries by generating Boolean search formulations automatically using term frequency considerations from natural language statements provided by system patrons. Experimental results are supplied and methods are described for applying automatic query formulation process in practice.…

Automatic detection and quantitative analysis of cells in the mouse primary motor cortex

NASA Astrophysics Data System (ADS)

Meng, Yunlong; He, Yong; Wu, Jingpeng; Chen, Shangbin; Li, Anan; Gong, Hui

2014-09-01

Neuronal cells play very important role on metabolism regulation and mechanism control, so cell number is a fundamental determinant of brain function. Combined suitable cell-labeling approaches with recently proposed three-dimensional optical imaging techniques, whole mouse brain coronal sections can be acquired with 1-μm voxel resolution. We have developed a completely automatic pipeline to perform cell centroids detection, and provided three-dimensional quantitative information of cells in the primary motor cortex of C57BL/6 mouse. It involves four principal steps: i) preprocessing; ii) image binarization; iii) cell centroids extraction and contour segmentation; iv) laminar density estimation. Investigations on the presented method reveal promising detection accuracy in terms of recall and precision, with average recall rate 92.1% and average precision rate 86.2%. We also analyze laminar density distribution of cells from pial surface to corpus callosum from the output vectorizations of detected cell centroids in mouse primary motor cortex, and find significant cellular density distribution variations in different layers. This automatic cell centroids detection approach will be beneficial for fast cell-counting and accurate density estimation, as time-consuming and error-prone manual identification is avoided.

Real-time management of faulty electrodes in electrical impedance tomography.

PubMed

Hartinger, Alzbeta E; Guardo, Robert; Adler, Andy; Gagnon, Hervé

2009-02-01

Completely or partially disconnected electrodes are a fairly common occurrence in many electrical impedance tomography (EIT) clinical applications. Several factors can contribute to electrode disconnection: patient movement, perspiration, manipulations by clinical staff, and defective electrode leads or electronics. By corrupting several measurements, faulty electrodes introduce significant image artifacts. In order to properly manage faulty electrodes, it is necessary to: 1) account for invalid data in image reconstruction algorithms and 2) automatically detect faulty electrodes. This paper presents a two-part approach for real-time management of faulty electrodes based on the principle of voltage-current reciprocity. The first part allows accounting for faulty electrodes in EIT image reconstruction without a priori knowledge of which electrodes are at fault. The method properly weights each measurement according to its compliance with the principle of voltage-current reciprocity. Results show that the algorithm is able to automatically determine the valid portion of the data and use it to calculate high-quality images. The second part of the approach allows automatic real-time detection of at least one faulty electrode with 100% sensitivity and two faulty electrodes with 80% sensitivity enabling the clinical staff to fix the problem as soon as possible to minimize data loss.

Using the EZ-Diffusion Model to Score a Single-Category Implicit Association Test of Physical Activity

PubMed Central

Rebar, Amanda L.; Ram, Nilam; Conroy, David E.

2014-01-01

Objective The Single-Category Implicit Association Test (SC-IAT) has been used as a method for assessing automatic evaluations of physical activity, but measurement artifact or consciously-held attitudes could be confounding the outcome scores of these measures. The objective of these two studies was to address these measurement concerns by testing the validity of a novel SC-IAT scoring technique. Design Study 1 was a cross-sectional study, and study 2 was a prospective study. Method In study 1, undergraduate students (N = 104) completed SC-IATs for physical activity, flowers, and sedentary behavior. In study 2, undergraduate students (N = 91) completed a SC-IAT for physical activity, self-reported affective and instrumental attitudes toward physical activity, physical activity intentions, and wore an accelerometer for two weeks. The EZ-diffusion model was used to decompose the SC-IAT into three process component scores including the information processing efficiency score. Results In study 1, a series of structural equation model comparisons revealed that the information processing score did not share variability across distinct SC-IATs, suggesting it does not represent systematic measurement artifact. In study 2, the information processing efficiency score was shown to be unrelated to self-reported affective and instrumental attitudes toward physical activity, and positively related to physical activity behavior, above and beyond the traditional D-score of the SC-IAT. Conclusions The information processing efficiency score is a valid measure of automatic evaluations of physical activity. PMID:25484621

POPCORN: a Supervisory Control Simulation for Workload and Performance Research

NASA Technical Reports Server (NTRS)

Hart, S. G.; Battiste, V.; Lester, P. T.

1984-01-01

A multi-task simulation of a semi-automatic supervisory control system was developed to provide an environment in which training, operator strategy development, failure detection and resolution, levels of automation, and operator workload can be investigated. The goal was to develop a well-defined, but realistically complex, task that would lend itself to model-based analysis. The name of the task (POPCORN) reflects the visual display that depicts different task elements milling around waiting to be released and pop out to be performed. The operator's task was to complete each of 100 task elements that ere represented by different symbols, by selecting a target task and entering the desired a command. The simulated automatic system then completed the selected function automatically. Highly significant differences in performance, strategy, and rated workload were found as a function of all experimental manipulations (except reward/penalty).

PIGSPro: prediction of immunoGlobulin structures v2.

PubMed

Lepore, Rosalba; Olimpieri, Pier P; Messih, Mario A; Tramontano, Anna

2017-07-03

PIGSpro is a significant upgrade of the popular PIGS server for the prediction of the structure of immunoglobulins. The software has been completely rewritten in python following a similar pipeline as in the original method, but including, at various steps, relevant modifications found to improve its prediction accuracy, as demonstrated here. The steps of the pipeline include the selection of the appropriate framework for predicting the conserved regions of the molecule by homology; the target template alignment for this portion of the molecule; the selection of the main chain conformation of the hypervariable loops according to the canonical structure model, the prediction of the third loop of the heavy chain (H3) for which complete canonical structures are not available and the packing of the light and heavy chain if derived from different templates. Each of these steps has been improved including updated methods developed along the years. Last but not least, the user interface has been completely redesigned and an automatic monthly update of the underlying database has been implemented. The method is available as a web server at http://biocomputing.it/pigspro. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Automatic tracking of labeled red blood cells in microchannels.

PubMed

Pinho, Diana; Lima, Rui; Pereira, Ana I; Gayubo, Fernando

2013-09-01

The current study proposes an automatic method for the segmentation and tracking of red blood cells flowing through a 100- μm glass capillary. The original images were obtained by means of a confocal system and then processed in MATLAB using the Image Processing Toolbox. The measurements obtained with the proposed automatic method were compared with the results determined by a manual tracking method. The comparison was performed by using both linear regressions and Bland-Altman analysis. The results have shown a good agreement between the two methods. Therefore, the proposed automatic method is a powerful way to provide rapid and accurate measurements for in vitro blood experiments in microchannels. Copyright © 2012 John Wiley & Sons, Ltd.

The Potential of Automatic Word Comparison for Historical Linguistics.

PubMed

List, Johann-Mattis; Greenhill, Simon J; Gray, Russell D

2017-01-01

The amount of data from languages spoken all over the world is rapidly increasing. Traditional manual methods in historical linguistics need to face the challenges brought by this influx of data. Automatic approaches to word comparison could provide invaluable help to pre-analyze data which can be later enhanced by experts. In this way, computational approaches can take care of the repetitive and schematic tasks leaving experts to concentrate on answering interesting questions. Here we test the potential of automatic methods to detect etymologically related words (cognates) in cross-linguistic data. Using a newly compiled database of expert cognate judgments across five different language families, we compare how well different automatic approaches distinguish related from unrelated words. Our results show that automatic methods can identify cognates with a very high degree of accuracy, reaching 89% for the best-performing method Infomap. We identify the specific strengths and weaknesses of these different methods and point to major challenges for future approaches. Current automatic approaches for cognate detection-although not perfect-could become an important component of future research in historical linguistics.

The Potential of Automatic Word Comparison for Historical Linguistics

PubMed Central

Greenhill, Simon J.; Gray, Russell D.

2017-01-01

The amount of data from languages spoken all over the world is rapidly increasing. Traditional manual methods in historical linguistics need to face the challenges brought by this influx of data. Automatic approaches to word comparison could provide invaluable help to pre-analyze data which can be later enhanced by experts. In this way, computational approaches can take care of the repetitive and schematic tasks leaving experts to concentrate on answering interesting questions. Here we test the potential of automatic methods to detect etymologically related words (cognates) in cross-linguistic data. Using a newly compiled database of expert cognate judgments across five different language families, we compare how well different automatic approaches distinguish related from unrelated words. Our results show that automatic methods can identify cognates with a very high degree of accuracy, reaching 89% for the best-performing method Infomap. We identify the specific strengths and weaknesses of these different methods and point to major challenges for future approaches. Current automatic approaches for cognate detection—although not perfect—could become an important component of future research in historical linguistics. PMID:28129337

Recovery of chemical Estimates by Field Inhomogeneity Neighborhood Error Detection (REFINED): Fat/Water Separation at 7T

PubMed Central

Narayan, Sreenath; Kalhan, Satish C.; Wilson, David L.

2012-01-01

I.Abstract Purpose To reduce swaps in fat-water separation methods, a particular issue on 7T small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. Materials and Methods Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. Results Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. Conclusion Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. PMID:23023815

A Novel Method for Reconstructing Broken Contour Lines Extracted from Scanned Topographic Maps

NASA Astrophysics Data System (ADS)

Wang, Feng; Liu, Pingzhi; Yang, Yun; Wei, Haiping; An, Xiaoya

2018-05-01

It is known that after segmentation and morphological operations on scanned topographic maps, gaps occur in contour lines. It is also well known that filling these gaps and reconstruction of contour lines with high accuracy and completeness is not an easy problem. In this paper, a novel method is proposed dedicated in automatic or semiautomatic filling up caps and reconstructing broken contour lines in binary images. The key part of end points' auto-matching and reconnecting is deeply discussed after introducing the procedure of reconstruction, in which some key algorithms and mechanisms are presented and realized, including multiple incremental backing trace to get weighted average direction angle of end points, the max constraint angle control mechanism based on the multiple gradient ranks, combination of weighted Euclidean distance and deviation angle to determine the optimum matching end point, bidirectional parabola control, etc. Lastly, experimental comparisons based on typically samples are complemented between proposed method and the other representative method, the results indicate that the former holds higher accuracy and completeness, better stability and applicability.

Online automatic tuning and control for fed-batch cultivation

PubMed Central

van Straten, Gerrit; van der Pol, Leo A.; van Boxtel, Anton J. B.

2007-01-01

Performance of controllers applied in biotechnological production is often below expectation. Online automatic tuning has the capability to improve control performance by adjusting control parameters. This work presents automatic tuning approaches for model reference specific growth rate control during fed-batch cultivation. The approaches are direct methods that use the error between observed specific growth rate and its set point; systematic perturbations of the cultivation are not necessary. Two automatic tuning methods proved to be efficient, in which the adaptation rate is based on a combination of the error, squared error and integral error. These methods are relatively simple and robust against disturbances, parameter uncertainties, and initialization errors. Application of the specific growth rate controller yields a stable system. The controller and automatic tuning methods are qualified by simulations and laboratory experiments with Bordetella pertussis. PMID:18157554

Adherent Raindrop Modeling, Detectionand Removal in Video.

PubMed

You, Shaodi; Tan, Robby T; Kawakami, Rei; Mukaigawa, Yasuhiro; Ikeuchi, Katsushi

2016-09-01

Raindrops adhered to a windscreen or window glass can significantly degrade the visibility of a scene. Modeling, detecting and removing raindrops will, therefore, benefit many computer vision applications, particularly outdoor surveillance systems and intelligent vehicle systems. In this paper, a method that automatically detects and removes adherent raindrops is introduced. The core idea is to exploit the local spatio-temporal derivatives of raindrops. To accomplish the idea, we first model adherent raindrops using law of physics, and detect raindrops based on these models in combination with motion and intensity temporal derivatives of the input video. Having detected the raindrops, we remove them and restore the images based on an analysis that some areas of raindrops completely occludes the scene, and some other areas occlude only partially. For partially occluding areas, we restore them by retrieving as much as possible information of the scene, namely, by solving a blending function on the detected partially occluding areas using the temporal intensity derivative. For completely occluding areas, we recover them by using a video completion technique. Experimental results using various real videos show the effectiveness of our method.

A mixture model with a reference-based automatic selection of components for disease classification from protein and/or gene expression levels

PubMed Central

2011-01-01

Background Bioinformatics data analysis is often using linear mixture model representing samples as additive mixture of components. Properly constrained blind matrix factorization methods extract those components using mixture samples only. However, automatic selection of extracted components to be retained for classification analysis remains an open issue. Results The method proposed here is applied to well-studied protein and genomic datasets of ovarian, prostate and colon cancers to extract components for disease prediction. It achieves average sensitivities of: 96.2 (sd = 2.7%), 97.6% (sd = 2.8%) and 90.8% (sd = 5.5%) and average specificities of: 93.6% (sd = 4.1%), 99% (sd = 2.2%) and 79.4% (sd = 9.8%) in 100 independent two-fold cross-validations. Conclusions We propose an additive mixture model of a sample for feature extraction using, in principle, sparseness constrained factorization on a sample-by-sample basis. As opposed to that, existing methods factorize complete dataset simultaneously. The sample model is composed of a reference sample representing control and/or case (disease) groups and a test sample. Each sample is decomposed into two or more components that are selected automatically (without using label information) as control specific, case specific and not differentially expressed (neutral). The number of components is determined by cross-validation. Automatic assignment of features (m/z ratios or genes) to particular component is based on thresholds estimated from each sample directly. Due to the locality of decomposition, the strength of the expression of each feature across the samples can vary. Yet, they will still be allocated to the related disease and/or control specific component. Since label information is not used in the selection process, case and control specific components can be used for classification. That is not the case with standard factorization methods. Moreover, the component selected by proposed method as disease specific can be interpreted as a sub-mode and retained for further analysis to identify potential biomarkers. As opposed to standard matrix factorization methods this can be achieved on a sample (experiment)-by-sample basis. Postulating one or more components with indifferent features enables their removal from disease and control specific components on a sample-by-sample basis. This yields selected components with reduced complexity and generally, it increases prediction accuracy. PMID:22208882

Volumetric determination of uranium titanous sulfate as reductant before oxidimetric titration

USGS Publications Warehouse

Wahlberg, J.S.; Skinner, D.L.; Rader, L.F.

1957-01-01

Need for a more rapid volumetric method for the routine determination of uranium in uranium-rich materials has led to the development of a method that uses titanous sulfate as a reductant before oxidimetric titration. Separation of the hydrogen sulfide group is not necessary. Interfering elements precipitated by cupferron are removed by automatic filtrations made simultaneously rather than by the longer chloroform extraction method. Uranium is reduced from VI to IV by addition of an excess of titanous sulfate solution, cupric ion serving as an indicator by forming red metallic copper when reduction is complete. The copper is reoxidized by addition of mercuric perchlorate. The reduced uranium is then determined by addition of excess ferric sulfate and titration with ceric sulfate. The method has proved to be rapid, accurate, and economical.

Automatic rule generation for high-level vision

NASA Technical Reports Server (NTRS)

Rhee, Frank Chung-Hoon; Krishnapuram, Raghu

1992-01-01

A new fuzzy set based technique that was developed for decision making is discussed. It is a method to generate fuzzy decision rules automatically for image analysis. This paper proposes a method to generate rule-based approaches to solve problems such as autonomous navigation and image understanding automatically from training data. The proposed method is also capable of filtering out irrelevant features and criteria from the rules.

When wanting to change is not enough: automatic appetitive processes moderate the effects of a brief alcohol intervention in hazardous-drinking college students.

PubMed

Ostafin, Brian D; Palfai, Tibor P

2012-12-07

Research indicates that brief motivational interventions are efficacious treatments for hazardous drinking. Little is known, however, about the psychological processes that may moderate intervention success. Based on growing evidence that drinking behavior may be influenced by automatic (nonvolitional) mental processes, the current study examined whether automatic alcohol-approach associations moderated the effect of a brief motivational intervention. Specifically, we examined whether the efficacy of a single-session intervention designed to increase motivation to reduce alcohol consumption would be moderated by the strength of participants' automatic alcohol-approach associations. Eighty-seven undergraduate hazardous drinkers participated for course credit. Participants completed an Implicit Association Test to measure automatic alcohol-approach associations, a baseline measure of readiness to change drinking behavior, and measures of alcohol involvement. Participants were then randomly assigned to either a brief (15-minute) motivational intervention or a control condition. Participants completed a measure of readiness to change drinking at the end of the first session and returned for a follow-up session six weeks later in which they reported on their drinking over the previous month. Compared with the control group, those in the intervention condition showed higher readiness to change drinking at the end of the baseline session but did not show decreased drinking quantity at follow-up. Automatic alcohol-approach associations moderated the effects of the intervention on change in drinking quantity. Among participants in the intervention group, those with weak automatic alcohol-approach associations showed greater reductions in the amount of alcohol consumed per occasion at follow-up compared with those with strong automatic alcohol-approach associations. Automatic appetitive associations with alcohol were not related with change in amount of alcohol consumed per occasion in control participants. Furthermore, among participants who showed higher readiness to change, those who exhibited weaker alcohol-approach associations showed greater reductions in drinking quantity compared with those who exhibited stronger alcohol-approach associations. The results support the idea that automatic mental processes may moderate the influence of brief motivational interventions on quantity of alcohol consumed per drinking occasion. The findings suggest that intervention efficacy may be improved by utilizing implicit measures to identify those who may be responsive to brief interventions and by developing intervention elements to address the influence of automatic processes on drinking behavior.

Applications of luminescent systems to infectious disease methodology

NASA Technical Reports Server (NTRS)

Picciolo, G. L.; Chappelle, E. W.; Deming, J. W.; Mcgarry, M. A.; Nibley, D. A.; Okrend, H.; Thomas, R. R.

1976-01-01

The characterization of a clinical sample by a simple, fast, accurate, automatable analytical measurement is important in the management of infectious disease. Luminescence assays offer methods rich with options for these measurements. The instrumentation is common to each assay, and the investment is reasonable. Three general procedures were developed to varying degrees of completeness which measure bacterial levels by measuring their ATP, FMN and iron porphyrins. Bacteriuria detection and antibiograms can be determined within half a day. The characterization of the sample for its soluble ATP, FMN or prophyrins was also performed.

Machine Beats Experts: Automatic Discovery of Skill Models for Data-Driven Online Course Refinement

ERIC Educational Resources Information Center

Matsuda, Noboru; Furukawa, Tadanobu; Bier, Norman; Faloutsos, Christos

2015-01-01

How can we automatically determine which skills must be mastered for the successful completion of an online course? Large-scale online courses (e.g., MOOCs) often contain a broad range of contents frequently intended to be a semester's worth of materials; this breadth often makes it difficult to articulate an accurate set of skills and knowledge…

Automatic Astrometric and Photometric Calibration with SCAMP

NASA Astrophysics Data System (ADS)

Bertin, E.

2006-07-01

Astrometric and photometric calibrations have remained the most tiresome step in the reduction of large imaging surveys. I present a new software package, SCAMP which has been written to address this problem. SCAMP efficiently computes accurate astrometric and photometric solutions for any arbitrary sequence of FITS images in a completely automatic way. SCAMP is released under the GNU General Public Licence.

Assisting People with Developmental Disabilities to Improve Computer Pointing Efficiency through Multiple Mice and Automatic Pointing Assistive Programs

ERIC Educational Resources Information Center

Shih, Ching-Hsiang

2011-01-01

This study combines multi-mice technology (people with disabilities can use standard mice, instead of specialized alternative computer input devices, to achieve complete mouse operation) with an assistive pointing function (i.e. cursor-capturing, which enables the user to move the cursor to the target center automatically), to assess whether two…

Carotid stenosis assessment with multi-detector CT angiography: comparison between manual and automatic segmentation methods.

PubMed

Zhu, Chengcheng; Patterson, Andrew J; Thomas, Owen M; Sadat, Umar; Graves, Martin J; Gillard, Jonathan H

2013-04-01

Luminal stenosis is used for selecting the optimal management strategy for patients with carotid artery disease. The aim of this study is to evaluate the reproducibility of carotid stenosis quantification using manual and automated segmentation methods using submillimeter through-plane resolution Multi-Detector CT angiography (MDCTA). 35 patients having carotid artery disease with >30 % luminal stenosis as identified by carotid duplex imaging underwent contrast enhanced MDCTA. Two experienced CT readers quantified carotid stenosis from axial source images, reconstructed maximum intensity projection (MIP) and 3D-carotid geometry which was automatically segmented by an open-source toolkit (Vascular Modelling Toolkit, VMTK) using NASCET criteria. Good agreement among the measurement using axial images, MIP and automatic segmentation was observed. Automatic segmentation methods show better inter-observer agreement between the readers (intra-class correlation coefficient (ICC): 0.99 for diameter stenosis measurement) than manual measurement of axial (ICC = 0.82) and MIP (ICC = 0.86) images. Carotid stenosis quantification using an automatic segmentation method has higher reproducibility compared with manual methods.

Validation of semi-automatic segmentation of the left atrium

NASA Astrophysics Data System (ADS)

Rettmann, M. E.; Holmes, D. R., III; Camp, J. J.; Packer, D. L.; Robb, R. A.

2008-03-01

Catheter ablation therapy has become increasingly popular for the treatment of left atrial fibrillation. The effect of this treatment on left atrial morphology, however, has not yet been completely quantified. Initial studies have indicated a decrease in left atrial size with a concomitant decrease in pulmonary vein diameter. In order to effectively study if catheter based therapies affect left atrial geometry, robust segmentations with minimal user interaction are required. In this work, we validate a method to semi-automatically segment the left atrium from computed-tomography scans. The first step of the technique utilizes seeded region growing to extract the entire blood pool including the four chambers of the heart, the pulmonary veins, aorta, superior vena cava, inferior vena cava, and other surrounding structures. Next, the left atrium and pulmonary veins are separated from the rest of the blood pool using an algorithm that searches for thin connections between user defined points in the volumetric data or on a surface rendering. Finally, pulmonary veins are separated from the left atrium using a three dimensional tracing tool. A single user segmented three datasets three times using both the semi-automatic technique as well as manual tracing. The user interaction time for the semi-automatic technique was approximately forty-five minutes per dataset and the manual tracing required between four and eight hours per dataset depending on the number of slices. A truth model was generated using a simple voting scheme on the repeated manual segmentations. A second user segmented each of the nine datasets using the semi-automatic technique only. Several metrics were computed to assess the agreement between the semi-automatic technique and the truth model including percent differences in left atrial volume, DICE overlap, and mean distance between the boundaries of the segmented left atria. Overall, the semi-automatic approach was demonstrated to be repeatable within and between raters, and accurate when compared to the truth model. Finally, we generated a visualization to assess the spatial variability in the segmentation errors between the semi-automatic approach and the truth model. The visualization demonstrates the highest errors occur at the boundaries between the left atium and pulmonary veins as well as the left atrium and left atrial appendage. In conclusion, we describe a semi-automatic approach for left atrial segmentation that demonstrates repeatability and accuracy, with the advantage of significant time reduction in user interaction time.

Automatic crown cover mapping to improve forest inventory

Treesearch

Claude Vidal; Jean-Guy Boureau; Nicolas Robert; Nicolas Py; Josiane Zerubia; Xavier Descombes; Guillaume Perrin

2009-01-01

To automatically analyze near infrared aerial photographs, the French National Institute for Research in Computer Science and Control developed together with the French National Forest Inventory (NFI) a method for automatic crown cover mapping. This method uses a Reverse Jump Monte Carlo Markov Chain algorithm to locate the crowns and describe those using ellipses or...

Auspice: Automatic Service Planning in Cloud/Grid Environments

NASA Astrophysics Data System (ADS)

Chiu, David; Agrawal, Gagan

Recent scientific advances have fostered a mounting number of services and data sets available for utilization. These resources, though scattered across disparate locations, are often loosely coupled both semantically and operationally. This loosely coupled relationship implies the possibility of linking together operations and data sets to answer queries. This task, generally known as automatic service composition, therefore abstracts the process of complex scientific workflow planning from the user. We have been exploring a metadata-driven approach toward automatic service workflow composition, among other enabling mechanisms, in our system, Auspice: Automatic Service Planning in Cloud/Grid Environments. In this paper, we present a complete overview of our system's unique features and outlooks for future deployment as the Cloud computing paradigm becomes increasingly eminent in enabling scientific computing.

A fast and fully automatic registration approach based on point features for multi-source remote-sensing images

NASA Astrophysics Data System (ADS)

Yu, Le; Zhang, Dengrong; Holden, Eun-Jung

2008-07-01

Automatic registration of multi-source remote-sensing images is a difficult task as it must deal with the varying illuminations and resolutions of the images, different perspectives and the local deformations within the images. This paper proposes a fully automatic and fast non-rigid image registration technique that addresses those issues. The proposed technique performs a pre-registration process that coarsely aligns the input image to the reference image by automatically detecting their matching points by using the scale invariant feature transform (SIFT) method and an affine transformation model. Once the coarse registration is completed, it performs a fine-scale registration process based on a piecewise linear transformation technique using feature points that are detected by the Harris corner detector. The registration process firstly finds in succession, tie point pairs between the input and the reference image by detecting Harris corners and applying a cross-matching strategy based on a wavelet pyramid for a fast search speed. Tie point pairs with large errors are pruned by an error-checking step. The input image is then rectified by using triangulated irregular networks (TINs) to deal with irregular local deformations caused by the fluctuation of the terrain. For each triangular facet of the TIN, affine transformations are estimated and applied for rectification. Experiments with Quickbird, SPOT5, SPOT4, TM remote-sensing images of the Hangzhou area in China demonstrate the efficiency and the accuracy of the proposed technique for multi-source remote-sensing image registration.

An Automatic and Robust Algorithm of Reestablishment of Digital Dental Occlusion

PubMed Central

Chang, Yu-Bing; Xia, James J.; Gateno, Jaime; Xiong, Zixiang; Zhou, Xiaobo; Wong, Stephen T. C.

2017-01-01

In the field of craniomaxillofacial (CMF) surgery, surgical planning can be performed on composite 3-D models that are generated by merging a computerized tomography scan with digital dental models. Digital dental models can be generated by scanning the surfaces of plaster dental models or dental impressions with a high-resolution laser scanner. During the planning process, one of the essential steps is to reestablish the dental occlusion. Unfortunately, this task is time-consuming and often inaccurate. This paper presents a new approach to automatically and efficiently reestablish dental occlusion. It includes two steps. The first step is to initially position the models based on dental curves and a point matching technique. The second step is to reposition the models to the final desired occlusion based on iterative surface-based minimum distance mapping with collision constraints. With linearization of rotation matrix, the alignment is modeled by solving quadratic programming. The simulation was completed on 12 sets of digital dental models. Two sets of dental models were partially edentulous, and another two sets have first premolar extractions for orthodontic treatment. Two validation methods were applied to the articulated models. The results show that using our method, the dental models can be successfully articulated with a small degree of deviations from the occlusion achieved with the gold-standard method. PMID:20529735

Reducing the cost of dietary assessment: self-completed recall and analysis of nutrition for use with children (SCRAN24).

PubMed

Foster, E; Hawkins, A; Delve, J; Adamson, A J

2014-01-01

Self-Completed Recall and Analysis of Nutrition (scran24) is a prototype computerised 24-h recall system for use with 11-16 year olds. It is based on the Multiple Pass 24-h Recall method and includes prompts and checks throughout the system for forgotten food items. The development of scran24 was informed by an extensive literature review, a series of focus groups and usability testing. The first stage of the recall is a quick list where the user is asked to input all the foods and drinks they remember consuming the previous day. The quick list is structured into meals and snacks. Once the quick list is complete, additional information is collected on each food to determine food type and to obtain an estimate of portion size using digital images of food. Foods are located within the system using a free text search, which is linked to the information entered into the quick list. A time is assigned to each eating occasion using drag and drop onto a timeline. The system prompts the user if no foods or drinks have been consumed within a 3-h time frame, or if fewer than three drinks have been consumed throughout the day. The food composition code and weight (g) of all items selected are automatically allocated and stored. Nutritional information can be generated automatically via the scran24 companion Access database. scran24 was very well received by young people and was relatively quick to complete. The accuracy and precision was close to that of similar computer-based systems currently used in dietary studies. © 2013 The Authors Journal of Human Nutrition and Dietetics © 2013 The British Dietetic Association Ltd.

Enabling intelligent copernicus services for carbon and water balance modeling of boreal forest ecosystems - North State

NASA Astrophysics Data System (ADS)

Häme, Tuomas; Mutanen, Teemu; Rauste, Yrjö; Antropov, Oleg; Molinier, Matthieu; Quegan, Shaun; Kantzas, Euripides; Mäkelä, Annikki; Minunno, Francesco; Atli Benediktsson, Jon; Falco, Nicola; Arnason, Kolbeinn; Storvold, Rune; Haarpaintner, Jörg; Elsakov, Vladimir; Rasinmäki, Jussi

2015-04-01

The objective of project North State, funded by Framework Program 7 of the European Union, is to develop innovative data fusion methods that exploit the new generation of multi-source data from Sentinels and other satellites in an intelligent, self-learning framework. The remote sensing outputs are interfaced with state-of-the-art carbon and water flux models for monitoring the fluxes over boreal Europe to reduce current large uncertainties. This will provide a paradigm for the development of products for future Copernicus services. The models to be interfaced are a dynamic vegetation model and a light use efficiency model. We have identified four groups of variables that will be estimated with remote sensed data: land cover variables, forest characteristics, vegetation activity, and hydrological variables. The estimates will be used as model inputs and to validate the model outputs. The earth observation variables are computed as automatically as possible, with an objective to completely automatic estimation. North State has two sites for intensive studies in southern and northern Finland, respectively, one in Iceland and one in state Komi of Russia. Additionally, the model input variables will be estimated and models applied over European boreal and sub-arctic region from Ural Mountains to Iceland. The accuracy assessment of the earth observation variables will follow statistical sampling design. Model output predictions are compared to earth observation variables. Also flux tower measurements are applied in the model assessment. In the paper, results of hyperspectral, Sentinel-1, and Landsat data and their use in the models is presented. Also an example of a completely automatic land cover class prediction is reported.

Automatic alignment method for calibration of hydrometers

NASA Astrophysics Data System (ADS)

Lee, Y. J.; Chang, K. H.; Chon, J. C.; Oh, C. Y.

2004-04-01

This paper presents a new method to automatically align specific scale-marks for the calibration of hydrometers. A hydrometer calibration system adopting the new method consists of a vision system, a stepping motor, and software to control the system. The vision system is composed of a CCD camera and a frame grabber, and is used to acquire images. The stepping motor moves the camera, which is attached to the vessel containing a reference liquid, along the hydrometer. The operating program has two main functions: to process images from the camera to find the position of the horizontal plane and to control the stepping motor for the alignment of the horizontal plane with a particular scale-mark. Any system adopting this automatic alignment method is a convenient and precise means of calibrating a hydrometer. The performance of the proposed method is illustrated by comparing the calibration results using the automatic alignment method with those obtained using the manual method.

Improved automatic adjustment of density and contrast in FCR system using neural network

NASA Astrophysics Data System (ADS)

Takeo, Hideya; Nakajima, Nobuyoshi; Ishida, Masamitsu; Kato, Hisatoyo

1994-05-01

FCR system has an automatic adjustment of image density and contrast by analyzing the histogram of image data in the radiation field. Advanced image recognition methods proposed in this paper can improve the automatic adjustment performance, in which neural network technology is used. There are two methods. Both methods are basically used 3-layer neural network with back propagation. The image data are directly input to the input-layer in one method and the histogram data is input in the other method. The former is effective to the imaging menu such as shoulder joint in which the position of interest region occupied on the histogram changes by difference of positioning and the latter is effective to the imaging menu such as chest-pediatrics in which the histogram shape changes by difference of positioning. We experimentally confirm the validity of these methods (about the automatic adjustment performance) as compared with the conventional histogram analysis methods.

Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

PubMed

Zeng, Xueqiang; Luo, Gang

2017-12-01

Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

Automatic lumen segmentation in IVOCT images using binary morphological reconstruction

PubMed Central

2013-01-01

Background Atherosclerosis causes millions of deaths, annually yielding billions in expenses round the world. Intravascular Optical Coherence Tomography (IVOCT) is a medical imaging modality, which displays high resolution images of coronary cross-section. Nonetheless, quantitative information can only be obtained with segmentation; consequently, more adequate diagnostics, therapies and interventions can be provided. Since it is a relatively new modality, many different segmentation methods, available in the literature for other modalities, could be successfully applied to IVOCT images, improving accuracies and uses. Method An automatic lumen segmentation approach, based on Wavelet Transform and Mathematical Morphology, is presented. The methodology is divided into three main parts. First, the preprocessing stage attenuates and enhances undesirable and important information, respectively. Second, in the feature extraction block, wavelet is associated with an adapted version of Otsu threshold; hence, tissue information is discriminated and binarized. Finally, binary morphological reconstruction improves the binary information and constructs the binary lumen object. Results The evaluation was carried out by segmenting 290 challenging images from human and pig coronaries, and rabbit iliac arteries; the outcomes were compared with the gold standards made by experts. The resultant accuracy was obtained: True Positive (%) = 99.29 ± 2.96, False Positive (%) = 3.69 ± 2.88, False Negative (%) = 0.71 ± 2.96, Max False Positive Distance (mm) = 0.1 ± 0.07, Max False Negative Distance (mm) = 0.06 ± 0.1. Conclusions In conclusion, by segmenting a number of IVOCT images with various features, the proposed technique showed to be robust and more accurate than published studies; in addition, the method is completely automatic, providing a new tool for IVOCT segmentation. PMID:23937790

Standards for the Analysis and Processing of Surface-Water Data and Information Using Electronic Methods

USGS Publications Warehouse

Sauer, Vernon B.

2002-01-01

Surface-water computation methods and procedures are described in this report to provide standards from which a completely automated electronic processing system can be developed. To the greatest extent possible, the traditional U. S. Geological Survey (USGS) methodology and standards for streamflow data collection and analysis have been incorporated into these standards. Although USGS methodology and standards are the basis for this report, the report is applicable to other organizations doing similar work. The proposed electronic processing system allows field measurement data, including data stored on automatic field recording devices and data recorded by the field hydrographer (a person who collects streamflow and other surface-water data) in electronic field notebooks, to be input easily and automatically. A user of the electronic processing system easily can monitor the incoming data and verify and edit the data, if necessary. Input of the computational procedures, rating curves, shift requirements, and other special methods are interactive processes between the user and the electronic processing system, with much of this processing being automatic. Special computation procedures are provided for complex stations such as velocity-index, slope, control structures, and unsteady-flow models, such as the Branch-Network Dynamic Flow Model (BRANCH). Navigation paths are designed to lead the user through the computational steps for each type of gaging station (stage-only, stagedischarge, velocity-index, slope, rate-of-change in stage, reservoir, tide, structure, and hydraulic model stations). The proposed electronic processing system emphasizes the use of interactive graphics to provide good visual tools for unit values editing, rating curve and shift analysis, hydrograph comparisons, data-estimation procedures, data review, and other needs. Documentation, review, finalization, and publication of records are provided for with the electronic processing system, as well as archiving, quality assurance, and quality control.

Surgical gesture classification from video and kinematic data.

PubMed

Zappella, Luca; Béjar, Benjamín; Hager, Gregory; Vidal, René

2013-10-01

Much of the existing work on automatic classification of gestures and skill in robotic surgery is based on dynamic cues (e.g., time to completion, speed, forces, torque) or kinematic data (e.g., robot trajectories and velocities). While videos could be equally or more discriminative (e.g., videos contain semantic information not present in kinematic data), they are typically not used because of the difficulties associated with automatic video interpretation. In this paper, we propose several methods for automatic surgical gesture classification from video data. We assume that the video of a surgical task (e.g., suturing) has been segmented into video clips corresponding to a single gesture (e.g., grabbing the needle, passing the needle) and propose three methods to classify the gesture of each video clip. In the first one, we model each video clip as the output of a linear dynamical system (LDS) and use metrics in the space of LDSs to classify new video clips. In the second one, we use spatio-temporal features extracted from each video clip to learn a dictionary of spatio-temporal words, and use a bag-of-features (BoF) approach to classify new video clips. In the third one, we use multiple kernel learning (MKL) to combine the LDS and BoF approaches. Since the LDS approach is also applicable to kinematic data, we also use MKL to combine both types of data in order to exploit their complementarity. Our experiments on a typical surgical training setup show that methods based on video data perform equally well, if not better, than state-of-the-art approaches based on kinematic data. In turn, the combination of both kinematic and video data outperforms any other algorithm based on one type of data alone. Copyright © 2013 Elsevier B.V. All rights reserved.

Fully automatic and reference-marker-free image stitching method for full-spine and full-leg imaging with computed radiography

NASA Astrophysics Data System (ADS)

Wang, Xiaohui; Foos, David H.; Doran, James; Rogers, Michael K.

2004-05-01

Full-leg and full-spine imaging with standard computed radiography (CR) systems requires several cassettes/storage phosphor screens to be placed in a staggered arrangement and exposed simultaneously to achieve an increased imaging area. A method has been developed that can automatically and accurately stitch the acquired sub-images without relying on any external reference markers. It can detect and correct the order, orientation, and overlap arrangement of the subimages for stitching. The automatic determination of the order, orientation, and overlap arrangement of the sub-images consists of (1) constructing a hypothesis list that includes all cassette/screen arrangements, (2) refining hypotheses based on a set of rules derived from imaging physics, (3) correlating each consecutive sub-image pair in each hypothesis and establishing an overall figure-of-merit, (4) selecting the hypothesis of maximum figure-of-merit. The stitching process requires the CR reader to over scan each CR screen so that the screen edges are completely visible in the acquired sub-images. The rotational displacement and vertical displacement between two consecutive sub-images are calculated by matching the orientation and location of the screen edge in the front image and its corresponding shadow in the back image. The horizontal displacement is estimated by maximizing the correlation function between the two image sections in the overlap region. Accordingly, the two images are stitched together. This process is repeated for the newly stitched composite image and the next consecutive sub-image until a full-image composite is created. The method has been evaluated in both phantom experiments and clinical studies. The standard deviation of image misregistration is below one image pixel.

Automatic patient alignment system using 3D ultrasound.

PubMed

Kaar, Marcus; Figl, Michael; Hoffmann, Rainer; Birkfellner, Wolfgang; Stock, Markus; Georg, Dietmar; Goldner, Gregor; Hummel, Johann

2013-04-01

Recent developments in radiation therapy such as intensity modulated radiotherapy (IMRT) or dose painting promise to provide better dose distribution on the tumor. For effective application of these methods the exact positioning of the patient and the localization of the irradiated organ and surrounding structures is crucial. Especially with respect to the treatment of the prostate, ultrasound (US) allows for differentiation between soft tissue and was therefore applied by various repositioning systems, such as BAT or Clarity. The authors built a new system which uses 3D US at both sites, the CT room and the intervention room and applied a 3D/3D US/US registration for automatic repositioning. In a first step the authors applied image preprocessing methods to prepare the US images for an optimal registration process. For the 3D/3D registration procedure five different metrics were evaluated. To find the image metric which fits best for a particular patient three 3D US images were taken at the CT site and registered to each other. From these results an US registration error was calculated. The most successful image metric was then applied for the US/US registration process. The success of the whole repositioning method was assessed by taking the results of an ExacTrac system as golden standard. The US/US registration error was found to be 2.99 ± 1.54 mm with respect to the mutual information metric by Mattes (eleven patients) which revealed to be the most suitable of the assessed metrics. For complete repositioning chain the error amounted to 4.15 ± 1.20 mm (ten patients). The authors developed a system for patient repositioning which works automatically without the necessity of user interaction with an accuracy which seems to be suitable for clinical application.

Application of a semi-automatic cartilage segmentation method for biomechanical modeling of the knee joint.

PubMed

Liukkonen, Mimmi K; Mononen, Mika E; Tanska, Petri; Saarakkala, Simo; Nieminen, Miika T; Korhonen, Rami K

2017-10-01

Manual segmentation of articular cartilage from knee joint 3D magnetic resonance images (MRI) is a time consuming and laborious task. Thus, automatic methods are needed for faster and reproducible segmentations. In the present study, we developed a semi-automatic segmentation method based on radial intensity profiles to generate 3D geometries of knee joint cartilage which were then used in computational biomechanical models of the knee joint. Six healthy volunteers were imaged with a 3T MRI device and their knee cartilages were segmented both manually and semi-automatically. The values of cartilage thicknesses and volumes produced by these two methods were compared. Furthermore, the influences of possible geometrical differences on cartilage stresses and strains in the knee were evaluated with finite element modeling. The semi-automatic segmentation and 3D geometry construction of one knee joint (menisci, femoral and tibial cartilages) was approximately two times faster than with manual segmentation. Differences in cartilage thicknesses, volumes, contact pressures, stresses, and strains between segmentation methods in femoral and tibial cartilage were mostly insignificant (p > 0.05) and random, i.e. there were no systematic differences between the methods. In conclusion, the devised semi-automatic segmentation method is a quick and accurate way to determine cartilage geometries; it may become a valuable tool for biomechanical modeling applications with large patient groups.

38. INTERIOR VIEW, BERK SWITCH TOWER, SOUTH NORWALK, SHOWING COMPLETE ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

38. INTERIOR VIEW, BERK SWITCH TOWER, SOUTH NORWALK, SHOWING COMPLETE SWITCH LEVER ASSEMBLAGE AND DISPLAY BOARD ON FRONT WALL - New York, New Haven & Hartford Railroad, Automatic Signalization System, Long Island Sound shoreline between Stamford & New Haven, Stamford, Fairfield County, CT

Automatic segmentation of MR brain images of preterm infants using supervised classification.

PubMed

Moeskops, Pim; Benders, Manon J N L; Chiţ, Sabina M; Kersbergen, Karina J; Groenendaal, Floris; de Vries, Linda S; Viergever, Max A; Išgum, Ivana

2015-09-01

Preterm birth is often associated with impaired brain development. The state and expected progression of preterm brain development can be evaluated using quantitative assessment of MR images. Such measurements require accurate segmentation of different tissue types in those images. This paper presents an algorithm for the automatic segmentation of unmyelinated white matter (WM), cortical grey matter (GM), and cerebrospinal fluid in the extracerebral space (CSF). The algorithm uses supervised voxel classification in three subsequent stages. In the first stage, voxels that can easily be assigned to one of the three tissue types are labelled. In the second stage, dedicated analysis of the remaining voxels is performed. The first and the second stages both use two-class classification for each tissue type separately. Possible inconsistencies that could result from these tissue-specific segmentation stages are resolved in the third stage, which performs multi-class classification. A set of T1- and T2-weighted images was analysed, but the optimised system performs automatic segmentation using a T2-weighted image only. We have investigated the performance of the algorithm when using training data randomly selected from completely annotated images as well as when using training data from only partially annotated images. The method was evaluated on images of preterm infants acquired at 30 and 40weeks postmenstrual age (PMA). When the method was trained using random selection from the completely annotated images, the average Dice coefficients were 0.95 for WM, 0.81 for GM, and 0.89 for CSF on an independent set of images acquired at 30weeks PMA. When the method was trained using only the partially annotated images, the average Dice coefficients were 0.95 for WM, 0.78 for GM and 0.87 for CSF for the images acquired at 30weeks PMA, and 0.92 for WM, 0.80 for GM and 0.85 for CSF for the images acquired at 40weeks PMA. Even though the segmentations obtained using training data from the partially annotated images resulted in slightly lower Dice coefficients, the performance in all experiments was close to that of a second human expert (0.93 for WM, 0.79 for GM and 0.86 for CSF for the images acquired at 30weeks, and 0.94 for WM, 0.76 for GM and 0.87 for CSF for the images acquired at 40weeks). These results show that the presented method is robust to age and acquisition protocol and that it performs accurate segmentation of WM, GM, and CSF when the training data is extracted from complete annotations as well as when the training data is extracted from partial annotations only. This extends the applicability of the method by reducing the time and effort necessary to create training data in a population with different characteristics. Copyright © 2015 Elsevier Inc. All rights reserved.

Recovery of chemical estimates by field inhomogeneity neighborhood error detection (REFINED): fat/water separation at 7 tesla.

PubMed

Narayan, Sreenath; Kalhan, Satish C; Wilson, David L

2013-05-01

To reduce swaps in fat-water separation methods, a particular issue on 7 Tesla (T) small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. Copyright © 2012 Wiley Periodicals, Inc.

Automatic extraction of pavement markings on streets from point cloud data of mobile LiDAR

NASA Astrophysics Data System (ADS)

Gao, Yang; Zhong, Ruofei; Tang, Tao; Wang, Liuzhao; Liu, Xianlin

2017-08-01

Pavement markings provide an important foundation as they help to keep roads users safe. Accurate and comprehensive information about pavement markings assists the road regulators and is useful in developing driverless technology. Mobile light detection and ranging (LiDAR) systems offer new opportunities to collect and process accurate pavement markings’ information. Mobile LiDAR systems can directly obtain the three-dimensional (3D) coordinates of an object, thus defining spatial data and the intensity of (3D) objects in a fast and efficient way. The RGB attribute information of data points can be obtained based on the panoramic camera in the system. In this paper, we present a novel method process to automatically extract pavement markings using multiple attribute information of the laser scanning point cloud from the mobile LiDAR data. This method process utilizes a differential grayscale of RGB color, laser pulse reflection intensity, and the differential intensity to identify and extract pavement markings. We utilized point cloud density to remove the noise and used morphological operations to eliminate the errors. In the application, we tested our method process on different sections of roads in Beijing, China, and Buffalo, NY, USA. The results indicated that both correctness (p) and completeness (r) were higher than 90%. The method process of this research can be applied to extract pavement markings from huge point cloud data produced by mobile LiDAR.

BRAMS --- the Belgian RAdio Meteor Stations

NASA Astrophysics Data System (ADS)

Lamy, H.; Ranvier, S.; Martinez Picar, A.; Gamby, E.; Calders, S.; Anciaux, M.; De Keyser, J.

2014-07-01

BRAMS is a new radio observing facility developed by the Belgian Institute for Space Aeronomy (BISA) to detect and characterize meteors using forward scattering. It consists of a dedicated beacon located in the south-east of Belgium and in 25 identical receiving stations spread over the Belgian territory. The beacon transmits a pure sinusoidal wave at a frequency of 49.97 MHz with a power of 150 watts. A complete description of the BRAMS network and the data produced will be provided. The main scientific goals of the project are to compute fluxes, retrieve trajectories of individual objects, and determine physical parameters (speed, ionization, mass) for some of the observed meteor echoes. All these goals require a good knowledge of the radiation patterns of the transmitting and receiving antennas. Simulations have been made and will be validated with in-situ measurements using a UAV/drone equipped with a transmitter flying in the far-field region. The results will be provided. Each receiving station generates around 1 GB of data per day with typical numbers of sporadic meteor echoes of 1500--2000. An automatic detection method of these meteor echoes is therefore mandatory but is complicated by spurious echoes mostly due to airplanes. The latest developments of this automatic detection method will be presented and compared to manual counts for validation. Strong and weak points of the method will be presented as well as a possible alternative method using neural networks.

A method of automatic control procedures cardiopulmonary resuscitation

NASA Astrophysics Data System (ADS)

Bureev, A. Sh.; Zhdanov, D. S.; Kiseleva, E. Yu.; Kutsov, M. S.; Trifonov, A. Yu.

2015-11-01

The study is to present the results of works on creation of methods of automatic control procedures of cardiopulmonary resuscitation (CPR). A method of automatic control procedure of CPR by evaluating the acoustic data of the dynamics of blood flow in the bifurcation of carotid arteries and the dynamics of air flow in a trachea according to the current guidelines for CPR is presented. Evaluation of the patient is carried out by analyzing the respiratory noise and blood flow in the interspaces between the chest compressions and artificial pulmonary ventilation. The device operation algorithm of automatic control procedures of CPR and its block diagram has been developed.

Automatic color preference correction for color reproduction

NASA Astrophysics Data System (ADS)

Tsukada, Masato; Funayama, Chisato; Tajima, Johji

2000-12-01

The reproduction of natural objects in color images has attracted a great deal of attention. Reproduction more pleasing colors of natural objects is one of the methods available to improve image quality. We developed an automatic color correction method to maintain preferred color reproduction for three significant categories: facial skin color, green grass and blue sky. In this method, a representative color in an object area to be corrected is automatically extracted from an input image, and a set of color correction parameters is selected depending on the representative color. The improvement in image quality for reproductions of natural image was more than 93 percent in subjective experiments. These results show the usefulness of our automatic color correction method for the reproduction of preferred colors.

Space fabrication demonstration system, technical volume

NASA Technical Reports Server (NTRS)

1979-01-01

The automatic beam builder ABB was developed, fabricated, and demonstrated within the established contract cost and schedule constraints. The ABB demonstrated the feasibility of: producing lightweight beams automatically within the required rate of 1 to 5 ft of completed beam per minute and producing structurally sound beams with axial design load of 5538 N based on the Grumman photovoltaic satellite solar power system design reference structure.

Method for automatically evaluating a transition from a batch manufacturing technique to a lean manufacturing technique

DOEpatents

Ivezic, Nenad; Potok, Thomas E.

2003-09-30

A method for automatically evaluating a manufacturing technique comprises the steps of: receiving from a user manufacturing process step parameters characterizing a manufacturing process; accepting from the user a selection for an analysis of a particular lean manufacturing technique; automatically compiling process step data for each process step in the manufacturing process; automatically calculating process metrics from a summation of the compiled process step data for each process step; and, presenting the automatically calculated process metrics to the user. A method for evaluating a transition from a batch manufacturing technique to a lean manufacturing technique can comprise the steps of: collecting manufacturing process step characterization parameters; selecting a lean manufacturing technique for analysis; communicating the selected lean manufacturing technique and the manufacturing process step characterization parameters to an automatic manufacturing technique evaluation engine having a mathematical model for generating manufacturing technique evaluation data; and, using the lean manufacturing technique evaluation data to determine whether to transition from an existing manufacturing technique to the selected lean manufacturing technique.

Image processing based automatic diagnosis of glaucoma using wavelet features of segmented optic disc from fundus image.

PubMed

Singh, Anushikha; Dutta, Malay Kishore; ParthaSarathi, M; Uher, Vaclav; Burget, Radim

2016-02-01

Glaucoma is a disease of the retina which is one of the most common causes of permanent blindness worldwide. This paper presents an automatic image processing based method for glaucoma diagnosis from the digital fundus image. In this paper wavelet feature extraction has been followed by optimized genetic feature selection combined with several learning algorithms and various parameter settings. Unlike the existing research works where the features are considered from the complete fundus or a sub image of the fundus, this work is based on feature extraction from the segmented and blood vessel removed optic disc to improve the accuracy of identification. The experimental results presented in this paper indicate that the wavelet features of the segmented optic disc image are clinically more significant in comparison to features of the whole or sub fundus image in the detection of glaucoma from fundus image. Accuracy of glaucoma identification achieved in this work is 94.7% and a comparison with existing methods of glaucoma detection from fundus image indicates that the proposed approach has improved accuracy of classification. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Rules of engagement: incomplete and complete pronoun resolution.

PubMed

Love, Jessica; McKoon, Gail

2011-07-01

Research on shallow processing suggests that readers sometimes encode only a superficial representation of a text and fail to make use of all available information. Greene, McKoon, and Ratcliff (1992) extended this work to pronouns, finding evidence that readers sometimes fail to automatically identify referents even when these are unambiguous. In this paper we revisit those findings. In 11 recognition probe, priming, and self-report experiments, we manipulated Greene et al.'s stories to discover under what circumstances a pronoun's referent is automatically understood. We lengthened the stories from 4 to 8 lines. This simple manipulation led to automatic and correct resolution, which we attribute to readers' increased engagement with the stories. We found evidence of resolution even when the additional text did not mention the pronoun's referent. In addition, our results suggest that the pronoun temporarily boosts the referent's accessibility, an advantage that disappears by the end of the next sentence. Finally, we present evidence from memory experiments that supports complete pronoun resolution for the longer but not the shorter stories.

Is semantic priming (ir)rational? Insights from the speeded word fragment completion task.

PubMed

Heyman, Tom; Hutchison, Keith A; Storms, Gert

2016-10-01

Semantic priming, the phenomenon that a target is recognized faster if it is preceded by a semantically related prime, is a well-established effect. However, the mechanisms producing semantic priming are subject of debate. Several theories assume that the underlying processes are controllable and tuned to prime utility. In contrast, purely automatic processes, like automatic spreading activation, should be independent of the prime's usefulness. The present study sought to disentangle both accounts by creating a situation where prime processing is actually detrimental. Specifically, participants were asked to quickly complete word fragments with either the letter a or e (e.g., sh_ve to be completed as shave). Critical fragments were preceded by a prime that was either related (e.g., push) or unrelated (write) to a prohibited completion of the target (e.g., shove). In 2 experiments, we found a significant inhibitory priming effect, which is inconsistent with purely "rational" explanations of semantic priming. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Application test of a Detection Method for the Enclosed Turbine Runner Chamber

NASA Astrophysics Data System (ADS)

Liu, Yunlong; Shen, Dingjie; Xie, Yi; Yang, Xiangwei; Long, Yi; Li, Wenbo

2017-06-01

At present, for the existing problems of the testing methods for the key hidden metal components of the turbine runner chamber, such as the poor reliability, the inaccurate locating and the larger detection blind spots of the detection device, under the downtime without opening the cover of the hydropower turbine runner chamber, an automatic detection method based on real-time image acquisition and simulation comparison techniques was proposed. By using the permanent magnet wheel, the magnetic crawler which carry the real-time image acquisition device, could complete the crawling work on the inner surface of the enclosed chamber. Then the image acquisition device completed the real-time collection of the scene image of the enclosed chamber. According to the obtained location by using the positioning auxiliary device, the position of the real-time detection image in a virtual 3D model was calibrated. Through comparing of the real-time detection images and the computer simulation images, the defects or foreign matter fall into could be accurately positioning, so as to repair and clean up conveniently.

Automated Bone Segmentation and Surface Evaluation of a Small Animal Model of Post-Traumatic Osteoarthritis.

PubMed

Ramme, Austin J; Voss, Kevin; Lesporis, Jurinus; Lendhey, Matin S; Coughlin, Thomas R; Strauss, Eric J; Kennedy, Oran D

2017-05-01

MicroCT imaging allows for noninvasive microstructural evaluation of mineralized bone tissue, and is essential in studies of small animal models of bone and joint diseases. Automatic segmentation and evaluation of articular surfaces is challenging. Here, we present a novel method to create knee joint surface models, for the evaluation of PTOA-related joint changes in the rat using an atlas-based diffeomorphic registration to automatically isolate bone from surrounding tissues. As validation, two independent raters manually segment datasets and the resulting segmentations were compared to our novel automatic segmentation process. Data were evaluated using label map volumes, overlap metrics, Euclidean distance mapping, and a time trial. Intraclass correlation coefficients were calculated to compare methods, and were greater than 0.90. Total overlap, union overlap, and mean overlap were calculated to compare the automatic and manual methods and ranged from 0.85 to 0.99. A Euclidean distance comparison was also performed and showed no measurable difference between manual and automatic segmentations. Furthermore, our new method was 18 times faster than manual segmentation. Overall, this study describes a reliable, accurate, and automatic segmentation method for mineralized knee structures from microCT images, and will allow for efficient assessment of bony changes in small animal models of PTOA.

BRENDA in 2013: integrated reactions, kinetic data, enzyme function data, improved disease classification: new options and contents in BRENDA.

PubMed

Schomburg, Ida; Chang, Antje; Placzek, Sandra; Söhngen, Carola; Rother, Michael; Lang, Maren; Munaretto, Cornelia; Ulas, Susanne; Stelzer, Michael; Grote, Andreas; Scheer, Maurice; Schomburg, Dietmar

2013-01-01

The BRENDA (BRaunschweig ENzyme DAtabase) enzyme portal (http://www.brenda-enzymes.org) is the main information system of functional biochemical and molecular enzyme data and provides access to seven interconnected databases. BRENDA contains 2.7 million manually annotated data on enzyme occurrence, function, kinetics and molecular properties. Each entry is connected to a reference and the source organism. Enzyme ligands are stored with their structures and can be accessed via their names, synonyms or via a structure search. FRENDA (Full Reference ENzyme DAta) and AMENDA (Automatic Mining of ENzyme DAta) are based on text mining methods and represent a complete survey of PubMed abstracts with information on enzymes in different organisms, tissues or organelles. The supplemental database DRENDA provides more than 910 000 new EC number-disease relations in more than 510 000 references from automatic search and a classification of enzyme-disease-related information. KENDA (Kinetic ENzyme DAta), a new amendment extracts and displays kinetic values from PubMed abstracts. The integration of the EnzymeDetector offers an automatic comparison, evaluation and prediction of enzyme function annotations for prokaryotic genomes. The biochemical reaction database BKM-react contains non-redundant enzyme-catalysed and spontaneous reactions and was developed to facilitate and accelerate the construction of biochemical models.

A Pressure Plate-Based Method for the Automatic Assessment of Foot Strike Patterns During Running.

PubMed

Santuz, Alessandro; Ekizos, Antonis; Arampatzis, Adamantios

2016-05-01

The foot strike pattern (FSP, description of how the foot touches the ground at impact) is recognized to be a predictor of both performance and injury risk. The objective of the current investigation was to validate an original foot strike pattern assessment technique based on the numerical analysis of foot pressure distribution. We analyzed the strike patterns during running of 145 healthy men and women (85 male, 60 female). The participants ran on a treadmill with integrated pressure plate at three different speeds: preferred (shod and barefoot 2.8 ± 0.4 m/s), faster (shod 3.5 ± 0.6 m/s) and slower (shod 2.3 ± 0.3 m/s). A custom-designed algorithm allowed the automatic footprint recognition and FSP evaluation. Incomplete footprints were simultaneously identified and corrected from the software itself. The widely used technique of analyzing high-speed video recordings was checked for its reliability and has been used to validate the numerical technique. The automatic numerical approach showed a good conformity with the reference video-based technique (ICC = 0.93, p < 0.01). The great improvement in data throughput and the increased completeness of results allow the use of this software as a powerful feedback tool in a simple experimental setup.

Automatic building extraction from LiDAR data fusion of point and grid-based features

NASA Astrophysics Data System (ADS)

Du, Shouji; Zhang, Yunsheng; Zou, Zhengrong; Xu, Shenghua; He, Xue; Chen, Siyang

2017-08-01

This paper proposes a method for extracting buildings from LiDAR point cloud data by combining point-based and grid-based features. To accurately discriminate buildings from vegetation, a point feature based on the variance of normal vectors is proposed. For a robust building extraction, a graph cuts algorithm is employed to combine the used features and consider the neighbor contexture information. As grid feature computing and a graph cuts algorithm are performed on a grid structure, a feature-retained DSM interpolation method is proposed in this paper. The proposed method is validated by the benchmark ISPRS Test Project on Urban Classification and 3D Building Reconstruction and compared to the state-art-of-the methods. The evaluation shows that the proposed method can obtain a promising result both at area-level and at object-level. The method is further applied to the entire ISPRS dataset and to a real dataset of the Wuhan City. The results show a completeness of 94.9% and a correctness of 92.2% at the per-area level for the former dataset and a completeness of 94.4% and a correctness of 95.8% for the latter one. The proposed method has a good potential for large-size LiDAR data.

Efficient road geometry identification from digital vector data

NASA Astrophysics Data System (ADS)

Andrášik, Richard; Bíl, Michal

2016-07-01

A new method for the automatic identification of road geometry from digital vector data is presented. The method is capable of efficiently identifying circular curves with their radii and tangents (straight sections). The average error of identification ranged from 0.01 to 1.30 % for precisely drawn data and 4.81 % in the case of actual road data with noise in the location of vertices. The results demonstrate that the proposed method is faster and more precise than commonly used techniques. This approach can be used by road administrators to complete their databases with information concerning the geometry of roads. It can also be utilized by transport engineers or traffic safety analysts to investigate the possible dependence of traffic accidents on road geometries. The method presented is applicable as well to railroads and rivers or other line features.

Memory biases in remitted depression: the role of negative cognitions at explicit and automatic processing levels.

PubMed

Romero, Nuria; Sanchez, Alvaro; Vazquez, Carmelo

2014-03-01

Cognitive models propose that depression is caused by dysfunctional schemas that endure beyond the depressive episode, representing vulnerability factors for recurrence. However, research testing negative cognitions linked to dysfunctional schemas in formerly depressed individuals is still scarce. Furthermore, negative cognitions are presumed to be linked to biases in recalling negative self-referent information in formerly depressed individuals, but no studies have directly tested this association. In the present study, we evaluated differences between formerly and never-depressed individuals in several experimental indices of negative cognitions and their associations with the recall of emotional self-referent material. Formerly (n = 30) and never depressed individuals (n = 40) completed measures of explicit (i.e., scrambled sentence test) and automatic (i.e., lexical decision task) processing to evaluate negative cognitions. Furthermore participants completed a self-referent incidental recall task to evaluate memory biases. Formerly compared to never depressed individuals showed greater negative cognitions at both explicit and automatic levels of processing. Results also showed greater recall of negative self-referent information in formerly compared to never-depressed individuals. Finally, individual differences in negative cognitions at both explicit and automatic levels of processing predicted greater recall of negative self-referent material in formerly depressed individuals. Analyses of the relationship between explicit and automatic processing indices and memory biases were correlational and the majority of participants in both groups were women. Our findings provide evidence of negative cognitions in formerly depressed individuals at both automatic and explicit levels of processing that may confer a cognitive vulnerability to depression. Copyright © 2013 Elsevier Ltd. All rights reserved.

Leveraging Terminological Resources for Mapping between Rare Disease Information Sources

PubMed Central

Rance, Bastien; Snyder, Michelle; Lewis, Janine; Bodenreider, Olivier

2015-01-01

Background Rare disease information sources are incompletely and inconsistently cross-referenced to one another, making it difficult for information seekers to navigate across them. The development of such cross-references established manually by experts is generally labor intensive and costly. Objectives To develop an automatic mapping between two of the major rare diseases information sources, GARD and Orphanet, by leveraging terminological resources, especially the UMLS. Methods We map the rare disease terms from Orphanet and ORDR to the UMLS. We use the UMLS as a pivot to bridge between the rare disease terminologies. We compare our results to a mapping obtained through manually established cross-references to OMIM. Results Our mapping has a precision of 94%, a recall of 63% and an F1-score of 76%. Our automatic mapping should help facilitate the development of more complete and consistent cross-references between GARD and Orphanet, and is applicable to other rare disease information sources as well. PMID:23920611

A System for the Semantic Multimodal Analysis of News Audio-Visual Content

NASA Astrophysics Data System (ADS)

Mezaris, Vasileios; Gidaros, Spyros; Papadopoulos, GeorgiosTh; Kasper, Walter; Steffen, Jörg; Ordelman, Roeland; Huijbregts, Marijn; de Jong, Franciska; Kompatsiaris, Ioannis; Strintzis, MichaelG

2010-12-01

News-related content is nowadays among the most popular types of content for users in everyday applications. Although the generation and distribution of news content has become commonplace, due to the availability of inexpensive media capturing devices and the development of media sharing services targeting both professional and user-generated news content, the automatic analysis and annotation that is required for supporting intelligent search and delivery of this content remains an open issue. In this paper, a complete architecture for knowledge-assisted multimodal analysis of news-related multimedia content is presented, along with its constituent components. The proposed analysis architecture employs state-of-the-art methods for the analysis of each individual modality (visual, audio, text) separately and proposes a novel fusion technique based on the particular characteristics of news-related content for the combination of the individual modality analysis results. Experimental results on news broadcast video illustrate the usefulness of the proposed techniques in the automatic generation of semantic annotations.

Automatic Differentiation in Quantum Chemistry with Applications to Fully Variational Hartree-Fock.

PubMed

Tamayo-Mendoza, Teresa; Kreisbeck, Christoph; Lindh, Roland; Aspuru-Guzik, Alán

2018-05-23

Automatic differentiation (AD) is a powerful tool that allows calculating derivatives of implemented algorithms with respect to all of their parameters up to machine precision, without the need to explicitly add any additional functions. Thus, AD has great potential in quantum chemistry, where gradients are omnipresent but also difficult to obtain, and researchers typically spend a considerable amount of time finding suitable analytical forms when implementing derivatives. Here, we demonstrate that AD can be used to compute gradients with respect to any parameter throughout a complete quantum chemistry method. We present DiffiQult , a Hartree-Fock implementation, entirely differentiated with the use of AD tools. DiffiQult is a software package written in plain Python with minimal deviation from standard code which illustrates the capability of AD to save human effort and time in implementations of exact gradients in quantum chemistry. We leverage the obtained gradients to optimize the parameters of one-particle basis sets in the context of the floating Gaussian framework.

Ventricular tachycardia in post-myocardial infarction patients. Results of surgical therapy.

PubMed

Viganò, M; Martinelli, L; Salerno, J A; Minzioni, G; Chimienti, M; Graffigna, A; Goggi, C; Klersy, C; Montemartini, C

1986-05-01

This report addresses the problems related to surgical treatment of post-infarction ventricular tachycardia (VT) and is based on a 5 year experience of 36 consecutive patients. In every case the arrhythmia was unresponsive to pharmacological therapy. All patients were operated on after the completion of a diagnostic protocol including preoperative endocardial, intra-operative epi-endocardial mapping, the latter performed automatically when possible. Surgical techniques were: classical Guiraudon's encircling endocardial ventriculotomy (EEV); partial EEV, endocardial resection (ER); cryoablation or a combination of these procedures. The in-hospital mortality (30 days) was 8.3% (3 patients). During the follow-up period (1-68 months), 3 patients (9%) died of cardiac but not VT related causes. Of the survivors, 92% are VT-free. We consider electrophysiologically guided surgery a safe and reliable method for the treatment of post-infarction VT and suggest its more extensive use. We stress the importance of automatic mapping in pleomorphic and non-sustained VT, and the necessity of tailoring the surgical technique to the characteristics of each case.

Prevalence and functions of non-suicidal self-injury in Spanish adolescents.

PubMed

Calvete, Esther; Orue, Izaskun; Aizpuru, Leire; Brotherton, Hardin

2015-01-01

This study examined the prevalence, characteristics and functions of Non-suicidal Self-injury (NSSI) among Spanish adolescents. The sample consisted of 1,864 adolescents aged between 12 and 19 years (Mean Age = 15.32, SD = 1.97, 51.45% girls). The participants completed a modified version of the self-report scale Functional Assessment of Self-Mutilation (FASM; Lloyd, Kelley, & Hope, 1997) to assess rates and methods of NSSI used during the last 12 months. They also indicated the functions of NSSI. NSSI behaviors are common among Spanish adolescents. More than half of the sample showed such behavior in the past year, and 32.2% had carried out severe NSSI behaviors. The functions of NSSI were examined by using confirmatory factor analyses. Results supported a hierarchical model consisting of two second-order factors: automatic reinforcement, which explained both positive and negative automatic reinforcement, and social reinforcement, which explained both positive and negative social reinforcement. These dimensions are critical to understand the factors that maintain NSSI behavior and have implications for treatments.

Automatic lung lobe segmentation of COPD patients using iterative B-spline fitting

NASA Astrophysics Data System (ADS)

Shamonin, D. P.; Staring, M.; Bakker, M. E.; Xiao, C.; Stolk, J.; Reiber, J. H. C.; Stoel, B. C.

2012-02-01

We present an automatic lung lobe segmentation algorithm for COPD patients. The method enhances fissures, removes unlikely fissure candidates, after which a B-spline is fitted iteratively through the remaining candidate objects. The iterative fitting approach circumvents the need to classify each object as being part of the fissure or being noise, and allows the fissure to be detected in multiple disconnected parts. This property is beneficial for good performance in patient data, containing incomplete and disease-affected fissures. The proposed algorithm is tested on 22 COPD patients, resulting in accurate lobe-based densitometry, and a median overlap of the fissure (defined 3 voxels wide) with an expert ground truth of 0.65, 0.54 and 0.44 for the three main fissures. This compares to complete lobe overlaps of 0.99, 0.98, 0.98, 0.97 and 0.87 for the five main lobes, showing promise for lobe segmentation on data of patients with moderate to severe COPD.

Towards Virtual FLS: Development of a Peg Transfer Simulator

PubMed Central

Arikatla, Venkata S; Ahn, Woojin; Sankaranarayanan, Ganesh; De, Suvranu

2014-01-01

Background Peg transfer is one of five tasks in the Fundamentals of Laparoscopic Surgery (FLS), program. We report the development and validation of a Virtual Basic Laparoscopic Skill Trainer-Peg Transfer (VBLaST-PT©) simulator for automatic real-time scoring and objective quantification of performance. Methods We have introduced new techniques in order to allow bi-manual manipulation of pegs and automatic scoring/evaluation while maintaining high quality of simulation. We performed a preliminary face and construct validation study with 22 subjects divided into two groups: experts (PGY 4–5, fellow and practicing surgeons) and novice (PGY 1–3). Results Face validation shows high scores for all the aspects of the simulation. A two-tailed Mann-Whitney U-test scores showed significant difference between the two groups on completion time (p=0.003), FLS score (p=0.002) and the VBLaST-PT© score (p=0.006). Conclusions VBLaST-PT© is a high quality virtual simulator that showed both face and construct validity. PMID:24030904

Automatic Differentiation in Quantum Chemistry with Applications to Fully Variational Hartree–Fock

PubMed Central

2018-01-01

Automatic differentiation (AD) is a powerful tool that allows calculating derivatives of implemented algorithms with respect to all of their parameters up to machine precision, without the need to explicitly add any additional functions. Thus, AD has great potential in quantum chemistry, where gradients are omnipresent but also difficult to obtain, and researchers typically spend a considerable amount of time finding suitable analytical forms when implementing derivatives. Here, we demonstrate that AD can be used to compute gradients with respect to any parameter throughout a complete quantum chemistry method. We present DiffiQult, a Hartree–Fock implementation, entirely differentiated with the use of AD tools. DiffiQult is a software package written in plain Python with minimal deviation from standard code which illustrates the capability of AD to save human effort and time in implementations of exact gradients in quantum chemistry. We leverage the obtained gradients to optimize the parameters of one-particle basis sets in the context of the floating Gaussian framework.

Automatic comparison of striation marks and automatic classification of shoe prints

NASA Astrophysics Data System (ADS)

Geradts, Zeno J.; Keijzer, Jan; Keereweer, Isaac

1995-09-01

A database for toolmarks (named TRAX) and a database for footwear outsole designs (named REBEZO) have been developed on a PC. The databases are filled with video-images and administrative data about the toolmarks and the footwear designs. An algorithm for the automatic comparison of the digitized striation patterns has been developed for TRAX. The algorithm appears to work well for deep and complete striation marks and will be implemented in TRAX. For REBEZO some efforts have been made to the automatic classification of outsole patterns. The algorithm first segments the shoeprofile. Fourier-features are selected for the separate elements and are classified with a neural network. In future developments information on invariant moments of the shape and rotation angle will be included in the neural network.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zainudin, Mohd Lutfi, E-mail: mdlutfi07@gmail.com; Institut Matematik Kejuruteraan; Saaban, Azizan, E-mail: azizan.s@uum.edu.my

The solar radiation values have been composed by automatic weather station using the device that namely pyranometer. The device is functions to records all the radiation values that have been dispersed, and these data are very useful for it experimental works and solar device’s development. In addition, for modeling and designing on solar radiation system application is needed for complete data observation. Unfortunately, lack for obtained the complete solar radiation data frequently occur due to several technical problems, which mainly contributed by monitoring device. Into encountering this matter, estimation missing values in an effort to substitute absent values with imputedmore » data. This paper aimed to evaluate several piecewise interpolation techniques likes linear, splines, cubic, and nearest neighbor into dealing missing values in hourly solar radiation data. Then, proposed an extendable work into investigating the potential used of cubic Bezier technique and cubic Said-ball method as estimator tools. As result, methods for cubic Bezier and Said-ball perform the best compare to another piecewise imputation technique.« less

Benchmarking of hospital information systems: Monitoring of discharge letters and scheduling can reveal heterogeneities and time trends

PubMed Central

Dugas, Martin; Eckholt, Markus; Bunzemeier, Holger

2008-01-01

Background Monitoring of hospital information system (HIS) usage can provide insights into best practices within a hospital and help to assess time trends. In terms of effort and cost of benchmarking, figures derived automatically from the routine HIS system are preferable to manual methods like surveys, in particular for repeated analysis. Methods Due to relevance for quality management and efficient resource utilization we focused on time-to-completion of discharge letters (assessed by CT-plots) and usage of patient scheduling. We analyzed these parameters monthly during one year at a major university hospital in Germany. Results We found several distinct patterns of discharge letter documentation indicating a large heterogeneity of HIS usage between different specialties (completeness 51 – 99%, delays 0 – 90 days). Overall usage of scheduling increased during the observation period by 62%, but again showed a considerable variation between departments. Conclusion Regular monitoring of HIS key figures can contribute to a continuous HIS improvement process. PMID:18423046

10 CFR 431.134 - Uniform test methods for the measurement of energy consumption and water consumption of automatic...

Code of Federal Regulations, 2012 CFR

2012-01-01

... 10 Energy 3 2012-01-01 2012-01-01 false Uniform test methods for the measurement of energy consumption and water consumption of automatic commercial ice makers. 431.134 Section 431.134 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ENERGY EFFICIENCY PROGRAM FOR CERTAIN COMMERCIAL AND INDUSTRIAL EQUIPMENT Automatic Commercial Ice Makers Test...

10 CFR 431.134 - Uniform test methods for the measurement of energy consumption and water consumption of automatic...

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 3 2010-01-01 2010-01-01 false Uniform test methods for the measurement of energy consumption and water consumption of automatic commercial ice makers. 431.134 Section 431.134 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ENERGY EFFICIENCY PROGRAM FOR CERTAIN COMMERCIAL AND INDUSTRIAL EQUIPMENT Automatic Commercial Ice Makers Test...

A method for the automatic reconstruction of fetal cardiac signals from magnetocardiographic recordings

NASA Astrophysics Data System (ADS)

Mantini, D.; Alleva, G.; Comani, S.

2005-10-01

Fetal magnetocardiography (fMCG) allows monitoring the fetal heart function through algorithms able to retrieve the fetal cardiac signal, but no standardized automatic model has become available so far. In this paper, we describe an automatic method that restores the fetal cardiac trace from fMCG recordings by means of a weighted summation of fetal components separated with independent component analysis (ICA) and identified through dedicated algorithms that analyse the frequency content and temporal structure of each source signal. Multichannel fMCG datasets of 66 healthy and 4 arrhythmic fetuses were used to validate the automatic method with respect to a classical procedure requiring the manual classification of fetal components by an expert investigator. ICA was run with input clusters of different dimensions to simulate various MCG systems. Detection rates, true negative and false positive component categorization, QRS amplitude, standard deviation and signal-to-noise ratio of reconstructed fetal signals, and real and per cent QRS differences between paired fetal traces retrieved automatically and manually were calculated to quantify the performances of the automatic method. Its robustness and reliability, particularly evident with the use of large input clusters, might increase the diagnostic role of fMCG during the prenatal period.

Automatic image fusion of real-time ultrasound with computed tomography images: a prospective comparison between two auto-registration methods.

PubMed

Cha, Dong Ik; Lee, Min Woo; Kim, Ah Yeong; Kang, Tae Wook; Oh, Young-Taek; Jeong, Ja-Yeon; Chang, Jung-Woo; Ryu, Jiwon; Lee, Kyong Joon; Kim, Jaeil; Bang, Won-Chul; Shin, Dong Kuk; Choi, Sung Jin; Koh, Dalkwon; Seo, Bong Koo; Kim, Kyunga

2017-11-01

Background A major drawback of conventional manual image fusion is that the process may be complex, especially for less-experienced operators. Recently, two automatic image fusion techniques called Positioning and Sweeping auto-registration have been developed. Purpose To compare the accuracy and required time for image fusion of real-time ultrasonography (US) and computed tomography (CT) images between Positioning and Sweeping auto-registration. Material and Methods Eighteen consecutive patients referred for planning US for radiofrequency ablation or biopsy for focal hepatic lesions were enrolled. Image fusion using both auto-registration methods was performed for each patient. Registration error, time required for image fusion, and number of point locks used were compared using the Wilcoxon signed rank test. Results Image fusion was successful in all patients. Positioning auto-registration was significantly faster than Sweeping auto-registration for both initial (median, 11 s [range, 3-16 s] vs. 32 s [range, 21-38 s]; P < 0.001] and complete (median, 34.0 s [range, 26-66 s] vs. 47.5 s [range, 32-90]; P = 0.001] image fusion. Registration error of Positioning auto-registration was significantly higher for initial image fusion (median, 38.8 mm [range, 16.0-84.6 mm] vs. 18.2 mm [6.7-73.4 mm]; P = 0.029), but not for complete image fusion (median, 4.75 mm [range, 1.7-9.9 mm] vs. 5.8 mm [range, 2.0-13.0 mm]; P = 0.338]. Number of point locks required to refine the initially fused images was significantly higher with Positioning auto-registration (median, 2 [range, 2-3] vs. 1 [range, 1-2]; P = 0.012]. Conclusion Positioning auto-registration offers faster image fusion between real-time US and pre-procedural CT images than Sweeping auto-registration. The final registration error is similar between the two methods.

Automatic video shot boundary detection using k-means clustering and improved adaptive dual threshold comparison

NASA Astrophysics Data System (ADS)

Sa, Qila; Wang, Zhihui

2018-03-01

At present, content-based video retrieval (CBVR) is the most mainstream video retrieval method, using the video features of its own to perform automatic identification and retrieval. This method involves a key technology, i.e. shot segmentation. In this paper, the method of automatic video shot boundary detection with K-means clustering and improved adaptive dual threshold comparison is proposed. First, extract the visual features of every frame and divide them into two categories using K-means clustering algorithm, namely, one with significant change and one with no significant change. Then, as to the classification results, utilize the improved adaptive dual threshold comparison method to determine the abrupt as well as gradual shot boundaries.Finally, achieve automatic video shot boundary detection system.

Complete Numerical Solution of the Diffusion Equation of Random Genetic Drift

PubMed Central

Zhao, Lei; Yue, Xingye; Waxman, David

2013-01-01

A numerical method is presented to solve the diffusion equation for the random genetic drift that occurs at a single unlinked locus with two alleles. The method was designed to conserve probability, and the resulting numerical solution represents a probability distribution whose total probability is unity. We describe solutions of the diffusion equation whose total probability is unity as complete. Thus the numerical method introduced in this work produces complete solutions, and such solutions have the property that whenever fixation and loss can occur, they are automatically included within the solution. This feature demonstrates that the diffusion approximation can describe not only internal allele frequencies, but also the boundary frequencies zero and one. The numerical approach presented here constitutes a single inclusive framework from which to perform calculations for random genetic drift. It has a straightforward implementation, allowing it to be applied to a wide variety of problems, including those with time-dependent parameters, such as changing population sizes. As tests and illustrations of the numerical method, it is used to determine: (i) the probability density and time-dependent probability of fixation for a neutral locus in a population of constant size; (ii) the probability of fixation in the presence of selection; and (iii) the probability of fixation in the presence of selection and demographic change, the latter in the form of a changing population size. PMID:23749318

Augmenting atlas-based liver segmentation for radiotherapy treatment planning by incorporating image features proximal to the atlas contours

NASA Astrophysics Data System (ADS)

Li, Dengwang; Liu, Li; Chen, Jinhu; Li, Hongsheng; Yin, Yong; Ibragimov, Bulat; Xing, Lei

2017-01-01

Atlas-based segmentation utilizes a library of previously delineated contours of similar cases to facilitate automatic segmentation. The problem, however, remains challenging because of limited information carried by the contours in the library. In this studying, we developed a narrow-shell strategy to enhance the information of each contour in the library and to improve the accuracy of the exiting atlas-based approach. This study presented a new concept of atlas based segmentation method. Instead of using the complete volume of the target organs, only information along the organ contours from the atlas images was used for guiding segmentation of the new image. In setting up an atlas-based library, we included not only the coordinates of contour points, but also the image features adjacent to the contour. In this work, 139 CT images with normal appearing livers collected for radiotherapy treatment planning were used to construct the library. The CT images within the library were first registered to each other using affine registration. The nonlinear narrow shell was generated alongside the object contours of registered images. Matching voxels were selected inside common narrow shell image features of a library case and a new case using a speed-up robust features (SURF) strategy. A deformable registration was then performed using a thin plate splines (TPS) technique. The contour associated with the library case was propagated automatically onto the new image by exploiting the deformation field vectors. The liver contour was finally obtained by employing level set based energy optimization within the narrow shell. The performance of the proposed method was evaluated by comparing quantitatively the auto-segmentation results with that delineated by physicians. A novel atlas-based segmentation technique with inclusion of neighborhood image features through the introduction of a narrow-shell surrounding the target objects was established. Application of the technique to 30 liver cases suggested that the technique was capable to reliably segment liver cases from CT, 4D-CT, and CBCT images with little human interaction. The accuracy and speed of the proposed method are quantitatively validated by comparing automatic segmentation results with the manual delineation results. The Jaccard similarity metric between the automatically generated liver contours obtained by the proposed method and the physician delineated results are on an average 90%-96% for planning images. Incorporation of image features into the library contours improves the currently available atlas-based auto-contouring techniques and provides a clinically practical solution for auto-segmentation. The proposed mountainous narrow shell atlas based method can achieve efficient automatic liver propagation for CT, 4D-CT and CBCT images with following treatment planning and should find widespread application in future treatment planning systems.

Augmenting atlas-based liver segmentation for radiotherapy treatment planning by incorporating image features proximal to the atlas contours.

PubMed

Li, Dengwang; Liu, Li; Chen, Jinhu; Li, Hongsheng; Yin, Yong; Ibragimov, Bulat; Xing, Lei

2017-01-07

Atlas-based segmentation utilizes a library of previously delineated contours of similar cases to facilitate automatic segmentation. The problem, however, remains challenging because of limited information carried by the contours in the library. In this studying, we developed a narrow-shell strategy to enhance the information of each contour in the library and to improve the accuracy of the exiting atlas-based approach. This study presented a new concept of atlas based segmentation method. Instead of using the complete volume of the target organs, only information along the organ contours from the atlas images was used for guiding segmentation of the new image. In setting up an atlas-based library, we included not only the coordinates of contour points, but also the image features adjacent to the contour. In this work, 139 CT images with normal appearing livers collected for radiotherapy treatment planning were used to construct the library. The CT images within the library were first registered to each other using affine registration. The nonlinear narrow shell was generated alongside the object contours of registered images. Matching voxels were selected inside common narrow shell image features of a library case and a new case using a speed-up robust features (SURF) strategy. A deformable registration was then performed using a thin plate splines (TPS) technique. The contour associated with the library case was propagated automatically onto the new image by exploiting the deformation field vectors. The liver contour was finally obtained by employing level set based energy optimization within the narrow shell. The performance of the proposed method was evaluated by comparing quantitatively the auto-segmentation results with that delineated by physicians. A novel atlas-based segmentation technique with inclusion of neighborhood image features through the introduction of a narrow-shell surrounding the target objects was established. Application of the technique to 30 liver cases suggested that the technique was capable to reliably segment liver cases from CT, 4D-CT, and CBCT images with little human interaction. The accuracy and speed of the proposed method are quantitatively validated by comparing automatic segmentation results with the manual delineation results. The Jaccard similarity metric between the automatically generated liver contours obtained by the proposed method and the physician delineated results are on an average 90%-96% for planning images. Incorporation of image features into the library contours improves the currently available atlas-based auto-contouring techniques and provides a clinically practical solution for auto-segmentation. The proposed mountainous narrow shell atlas based method can achieve efficient automatic liver propagation for CT, 4D-CT and CBCT images with following treatment planning and should find widespread application in future treatment planning systems.

[The mediating role of anger in the relationship between automatic thoughts and physical aggression in adolescents].

PubMed

Yavuzer, Yasemin; Karataş, Zeynep

2013-01-01

This study aimed to examine the mediating role of anger in the relationship between automatic thoughts and physical aggression in adolescents. The study included 224 adolescents in the 9th grade of 3 different high schools in central Burdur during the 2011-2012 academic year. Participants completed the Aggression Questionnaire and Automatic Thoughts Scale in their classrooms during counseling sessions. Data were analyzed using simple and multiple linear regression analysis. There were positive correlations between the adolescents' automatic thoughts, and physical aggression, and anger. According to regression analysis, automatic thoughts effectively predicted the level of physical aggression (b= 0.233, P < 0.001)) and anger (b= 0.325, P < 0.001). Analysis of the mediating role of anger showed that anger fully mediated the relationship between automatic thoughts and physical aggression (Sobel z = 5.646, P < 0.001). Anger fully mediated the relationship between automatic thoughts and physical aggression. Providing adolescents with anger management skills training is very important for the prevention of physical aggression. Such training programs should include components related to the development of an awareness of dysfunctional and anger-triggering automatic thoughts, and how to change them. As the study group included adolescents from Burdur, the findings can only be generalized to groups with similar characteristics.

A substitution method to improve completeness of events documentation in anesthesia records.

PubMed

Lamer, Antoine; De Jonckheere, Julien; Marcilly, Romaric; Tavernier, Benoît; Vallet, Benoît; Jeanne, Mathieu; Logier, Régis

2015-12-01

AIMS are optimized to find and display data and curves about one specific intervention but is not retrospective analysis on a huge volume of interventions. Such a system present two main limitation; (1) the transactional database architecture, (2) the completeness of documentation. In order to solve the architectural problem, data warehouses were developed to propose architecture suitable for analysis. However, completeness of documentation stays unsolved. In this paper, we describe a method which allows determining of substitution rules in order to detect missing anesthesia events in an anesthesia record. Our method is based on the principle that missing event could be detected using a substitution one defined as the nearest documented event. As an example, we focused on the automatic detection of the start and the end of anesthesia procedure when these events were not documented by the clinicians. We applied our method on a set of records in order to evaluate; (1) the event detection accuracy, (2) the improvement of valid records. For the year 2010-2012, we obtained event detection with a precision of 0.00 (-2.22; 2.00) min for the start of anesthesia and 0.10 (0.00; 0.35) min for the end of anesthesia. On the other hand, we increased by 21.1% the data completeness (from 80.3 to 97.2% of the total database) for the start and the end of anesthesia events. This method seems to be efficient to replace missing "start and end of anesthesia" events. This method could also be used to replace other missing time events in this particular data warehouse as well as in other kind of data warehouses.

Fully automatic multi-atlas segmentation of CTA for partial volume correction in cardiac SPECT/CT

NASA Astrophysics Data System (ADS)

Liu, Qingyi; Mohy-ud-Din, Hassan; Boutagy, Nabil E.; Jiang, Mingyan; Ren, Silin; Stendahl, John C.; Sinusas, Albert J.; Liu, Chi

2017-05-01

Anatomical-based partial volume correction (PVC) has been shown to improve image quality and quantitative accuracy in cardiac SPECT/CT. However, this method requires manual segmentation of various organs from contrast-enhanced computed tomography angiography (CTA) data. In order to achieve fully automatic CTA segmentation for clinical translation, we investigated the most common multi-atlas segmentation methods. We also modified the multi-atlas segmentation method by introducing a novel label fusion algorithm for multiple organ segmentation to eliminate overlap and gap voxels. To evaluate our proposed automatic segmentation, eight canine 99mTc-labeled red blood cell SPECT/CT datasets that incorporated PVC were analyzed, using the leave-one-out approach. The Dice similarity coefficient of each organ was computed. Compared to the conventional label fusion method, our proposed label fusion method effectively eliminated gaps and overlaps and improved the CTA segmentation accuracy. The anatomical-based PVC of cardiac SPECT images with automatic multi-atlas segmentation provided consistent image quality and quantitative estimation of intramyocardial blood volume, as compared to those derived using manual segmentation. In conclusion, our proposed automatic multi-atlas segmentation method of CTAs is feasible, practical, and facilitates anatomical-based PVC of cardiac SPECT/CT images.

Automatic programming of arc welding robots

NASA Astrophysics Data System (ADS)

Padmanabhan, Srikanth

Automatic programming of arc welding robots requires the geometric description of a part from a solid modeling system, expert weld process knowledge and the kinematic arrangement of the robot and positioner automatically. Current commercial solid models are incapable of storing explicitly product and process definitions of weld features. This work presents a paradigm to develop a computer-aided engineering environment that supports complete weld feature information in a solid model and to create an automatic programming system for robotic arc welding. In the first part, welding features are treated as properties or attributes of an object, features which are portions of the object surface--the topological boundary. The structure for representing the features and attributes is a graph called the Welding Attribute Graph (WAGRAPH). The method associates appropriate weld features to geometric primitives, adds welding attributes, and checks the validity of welding specifications. A systematic structure is provided to incorporate welding attributes and coordinate system information in a CSG tree. The specific implementation of this structure using a hybrid solid modeler (IDEAS) and an object-oriented programming paradigm is described. The second part provides a comprehensive methodology to acquire and represent weld process knowledge required for the proper selection of welding schedules. A methodology of knowledge acquisition using statistical methods is proposed. It is shown that these procedures did little to capture the private knowledge of experts (heuristics), but helped in determining general dependencies, and trends. A need was established for building the knowledge-based system using handbook knowledge and to allow the experts further to build the system. A methodology to check the consistency and validity for such knowledge addition is proposed. A mapping shell designed to transform the design features to application specific weld process schedules is described. A new approach using fixed path modified continuation methods is proposed in the final section to plan continuously the trajectory of weld seams in an integrated welding robot and positioner environment. The joint displacement, velocity, and acceleration histories all along the path as a function of the path parameter for the best possible welding condition are provided for the robot and the positioner to track various paths normally encountered in arc welding.

Method and system for entering data within a flight plan entry field

NASA Technical Reports Server (NTRS)

Gibbs, Michael J. (Inventor); Van Omen, Debi (Inventor); Adams, Michael B. (Inventor); Chase, Karl L. (Inventor); Lewis, Daniel E. (Inventor); McCrobie, Daniel E. (Inventor)

2005-01-01

The present invention provides systems, apparatus and methods for entering data into a flight plan entry field which facilitates the display and editing of aircraft flight-plan data. In one embodiment, the present invention provides a method for entering multiple waypoint and procedure identifiers at once within a single a flight plan entry field. In another embodiment, the present invention provides for the partial entry of any waypoint or procedure identifiers, and thereafter relating the identifiers with an aircraft's flight management system to anticipate the complete text entry for display. In yet another embodiment, the present invention discloses a method to automatically provide the aircraft operator with selectable prioritized arrival and approach routing identifiers by a single manual selection. In another embodiment, the present invention is a method for providing the aircraft operator with selectable alternate patterns to a new runway.

Adaptive variational mode decomposition method for signal processing based on mode characteristic

NASA Astrophysics Data System (ADS)

Lian, Jijian; Liu, Zhuo; Wang, Haijun; Dong, Xiaofeng

2018-07-01

Variational mode decomposition is a completely non-recursive decomposition model, where all the modes are extracted concurrently. However, the model requires a preset mode number, which limits the adaptability of the method since a large deviation in the number of mode set will cause the discard or mixing of the mode. Hence, a method called Adaptive Variational Mode Decomposition (AVMD) was proposed to automatically determine the mode number based on the characteristic of intrinsic mode function. The method was used to analyze the simulation signals and the measured signals in the hydropower plant. Comparisons have also been conducted to evaluate the performance by using VMD, EMD and EWT. It is indicated that the proposed method has strong adaptability and is robust to noise. It can determine the mode number appropriately without modulation even when the signal frequencies are relatively close.

A fully automatable enzymatic method for DNA extraction from plant tissues

PubMed Central

Manen, Jean-François; Sinitsyna, Olga; Aeschbach, Lorène; Markov, Alexander V; Sinitsyn, Arkady

2005-01-01

Background DNA extraction from plant tissues, unlike DNA isolation from mammalian tissues, remains difficult due to the presence of a rigid cell wall around the plant cells. Currently used methods inevitably require a laborious mechanical grinding step, necessary to disrupt the cell wall for the release of DNA. Results Using a cocktail of different carbohydrases, a method was developed that enables a complete digestion of the plant cell walls and subsequent DNA release. Optimized conditions for the digestion reaction minimize DNA shearing and digestion, and maximize DNA release from the plant cell. The method gave good results in 125 of the 156 tested species. Conclusion In combination with conventional DNA isolation techniques, the new enzymatic method allows to obtain high-yield, high-molecular weight DNA, which can be used for many applications, including genome characterization by AFLP, RAPD and SSR. Automation of the protocol (from leaf disks to DNA) is possible with existing workstations. PMID:16269076

Automatic target alignment of the Helios laser system

NASA Astrophysics Data System (ADS)

Liberman, I.; Viswanathan, V. K.; Klein, M.; Seery, B. D.

1980-05-01

An automatic target-alignment technique for the Helios laser facility is reported and verified experimentally. The desired alignment condition is completely described by an autocollimation test. A computer program examines the autocollimated return pattern from the surrogate target and correctly describes any changes required in mirror orientation to yield optimum target alignment with either aberrated or misaligned beams. Automated on-line target alignment is thus shown to be feasible.

System for definition of the central-chest vasculature

NASA Astrophysics Data System (ADS)

Taeprasartsit, Pinyo; Higgins, William E.

2009-02-01

Accurate definition of the central-chest vasculature from three-dimensional (3D) multi-detector CT (MDCT) images is important for pulmonary applications. For instance, the aorta and pulmonary artery help in automatic definition of the Mountain lymph-node stations for lung-cancer staging. This work presents a system for defining major vascular structures in the central chest. The system provides automatic methods for extracting the aorta and pulmonary artery and semi-automatic methods for extracting the other major central chest arteries/veins, such as the superior vena cava and azygos vein. Automatic aorta and pulmonary artery extraction are performed by model fitting and selection. The system also extracts certain vascular structure information to validate outputs. A semi-automatic method extracts vasculature by finding the medial axes between provided important sites. Results of the system are applied to lymph-node station definition and guidance of bronchoscopic biopsy.

a Method for the Seamlines Network Automatic Selection Based on Building Vector

NASA Astrophysics Data System (ADS)

Li, P.; Dong, Y.; Hu, Y.; Li, X.; Tan, P.

2018-04-01

In order to improve the efficiency of large scale orthophoto production of city, this paper presents a method for automatic selection of seamlines network in large scale orthophoto based on the buildings' vector. Firstly, a simple model of the building is built by combining building's vector, height and DEM, and the imaging area of the building on single DOM is obtained. Then, the initial Voronoi network of the measurement area is automatically generated based on the positions of the bottom of all images. Finally, the final seamlines network is obtained by optimizing all nodes and seamlines in the network automatically based on the imaging areas of the buildings. The experimental results show that the proposed method can not only get around the building seamlines network quickly, but also remain the Voronoi network' characteristics of projection distortion minimum theory, which can solve the problem of automatic selection of orthophoto seamlines network in image mosaicking effectively.

Methods of visualizing graphs

DOEpatents

Wong, Pak C.; Mackey, Patrick S.; Perrine, Kenneth A.; Foote, Harlan P.; Thomas, James J.

2008-12-23

Methods for visualizing a graph by automatically drawing elements of the graph as labels are disclosed. In one embodiment, the method comprises receiving node information and edge information from an input device and/or communication interface, constructing a graph layout based at least in part on that information, wherein the edges are automatically drawn as labels, and displaying the graph on a display device according to the graph layout. In some embodiments, the nodes are automatically drawn as labels instead of, or in addition to, the label-edges.

Occupational self-coding and automatic recording (OSCAR): a novel web-based tool to collect and code lifetime job histories in large population-based studies.

PubMed

De Matteis, Sara; Jarvis, Deborah; Young, Heather; Young, Alan; Allen, Naomi; Potts, James; Darnton, Andrew; Rushton, Lesley; Cullinan, Paul

2017-03-01

Objectives The standard approach to the assessment of occupational exposures is through the manual collection and coding of job histories. This method is time-consuming and costly and makes it potentially unfeasible to perform high quality analyses on occupational exposures in large population-based studies. Our aim was to develop a novel, efficient web-based tool to collect and code lifetime job histories in the UK Biobank, a population-based cohort of over 500 000 participants. Methods We developed OSCAR (occupations self-coding automatic recording) based on the hierarchical structure of the UK Standard Occupational Classification (SOC) 2000, which allows individuals to collect and automatically code their lifetime job histories via a simple decision-tree model. Participants were asked to find each of their jobs by selecting appropriate job categories until they identified their job title, which was linked to a hidden 4-digit SOC code. For each occupation a job title in free text was also collected to estimate Cohen's kappa (κ) inter-rater agreement between SOC codes assigned by OSCAR and an expert manual coder. Results OSCAR was administered to 324 653 UK Biobank participants with an existing email address between June and September 2015. Complete 4-digit SOC-coded lifetime job histories were collected for 108 784 participants (response rate: 34%). Agreement between the 4-digit SOC codes assigned by OSCAR and the manual coder for a random sample of 400 job titles was moderately good [κ=0.45, 95% confidence interval (95% CI) 0.42-0.49], and improved when broader job categories were considered (κ=0.64, 95% CI 0.61-0.69 at a 1-digit SOC-code level). Conclusions OSCAR is a novel, efficient, and reasonably reliable web-based tool for collecting and automatically coding lifetime job histories in large population-based studies. Further application in other research projects for external validation purposes is warranted.

A software tool to automatically assure and report daily treatment deliveries by a cobalt‐60 radiation therapy device

PubMed Central

Wooten, H. Omar; Green, Olga; Li, Harold H.; Liu, Shi; Li, Xiaoling; Rodriguez, Vivian; Mutic, Sasa; Kashani, Rojano

2016-01-01

The aims of this study were to develop a method for automatic and immediate verification of treatment delivery after each treatment fraction in order to detect and correct errors, and to develop a comprehensive daily report which includes delivery verification results, daily image‐guided radiation therapy (IGRT) review, and information for weekly physics reviews. After systematically analyzing the requirements for treatment delivery verification and understanding the available information from a commercial MRI‐guided radiotherapy treatment machine, we designed a procedure to use 1) treatment plan files, 2) delivery log files, and 3) beam output information to verify the accuracy and completeness of each daily treatment delivery. The procedure verifies the correctness of delivered treatment plan parameters including beams, beam segments and, for each segment, the beam‐on time and MLC leaf positions. For each beam, composite primary fluence maps are calculated from the MLC leaf positions and segment beam‐on time. Error statistics are calculated on the fluence difference maps between the plan and the delivery. A daily treatment delivery report is designed to include all required information for IGRT and weekly physics reviews including the plan and treatment fraction information, daily beam output information, and the treatment delivery verification results. A computer program was developed to implement the proposed procedure of the automatic delivery verification and daily report generation for an MRI guided radiation therapy system. The program was clinically commissioned. Sensitivity was measured with simulated errors. The final version has been integrated into the commercial version of the treatment delivery system. The method automatically verifies the EBRT treatment deliveries and generates the daily treatment reports. Already in clinical use for over one year, it is useful to facilitate delivery error detection, and to expedite physician daily IGRT review and physicist weekly chart review. PACS number(s): 87.55.km PMID:27167269

Automated Assessment of Cognitive Health Using Smart Home Technologies

PubMed Central

Dawadi, Prafulla N.; Cook, Diane J.; Schmitter-Edgecombe, Maureen; Parsey, Carolyn

2014-01-01

BACKGROUND The goal of this work is to develop intelligent systems to monitor the well being of individuals in their home environments. OBJECTIVE This paper introduces a machine learning-based method to automatically predict activity quality in smart homes and automatically assess cognitive health based on activity quality. METHODS This paper describes an automated framework to extract set of features from smart home sensors data that reflects the activity performance or ability of an individual to complete an activity which can be input to machine learning algorithms. Output from learning algorithms including principal component analysis, support vector machine, and logistic regression algorithms are used to quantify activity quality for a complex set of smart home activities and predict cognitive health of participants. RESULTS Smart home activity data was gathered from volunteer participants (n=263) who performed a complex set of activities in our smart home testbed. We compare our automated activity quality prediction and cognitive health prediction with direct observation scores and health assessment obtained from neuropsychologists. With all samples included, we obtained statistically significant correlation (r=0.54) between direct observation scores and predicted activity quality. Similarly, using a support vector machine classifier, we obtained reasonable classification accuracy (area under the ROC curve = 0.80, g-mean = 0.73) in classifying participants into two different cognitive classes, dementia and cognitive healthy. CONCLUSIONS The results suggest that it is possible to automatically quantify the task quality of smart home activities and perform limited assessment of the cognitive health of individual if smart home activities are properly chosen and learning algorithms are appropriately trained. PMID:23949177

Ratbot automatic navigation by electrical reward stimulation based on distance measurement in unknown environments.

PubMed

Gao, Liqiang; Sun, Chao; Zhang, Chen; Zheng, Nenggan; Chen, Weidong; Zheng, Xiaoxiang

2013-01-01

Traditional automatic navigation methods for bio-robots are constrained to configured environments and thus can't be applied to tasks in unknown environments. With no consideration of bio-robot's own innate living ability and treating bio-robots in the same way as mechanical robots, those methods neglect the intelligence behavior of animals. This paper proposes a novel ratbot automatic navigation method in unknown environments using only reward stimulation and distance measurement. By utilizing rat's habit of thigmotaxis and its reward-seeking behavior, this method is able to incorporate rat's intrinsic intelligence of obstacle avoidance and path searching into navigation. Experiment results show that this method works robustly and can successfully navigate the ratbot to a target in the unknown environment. This work might put a solid base for application of ratbots and also has significant implication of automatic navigation for other bio-robots as well.

Dr. Liver: A preoperative planning system of liver graft volumetry for living donor liver transplantation.

PubMed

Yang, Xiaopeng; Yang, Jae Do; Yu, Hee Chul; Choi, Younggeun; Yang, Kwangho; Lee, Tae Beom; Hwang, Hong Pil; Ahn, Sungwoo; You, Heecheon

2018-05-01

Manual tracing of the right and left liver lobes from computed tomography (CT) images for graft volumetry in preoperative surgery planning of living donor liver transplantation (LDLT) is common at most medical centers. This study aims to develop an automatic system with advanced image processing algorithms and user-friendly interfaces for liver graft volumetry and evaluate its accuracy and efficiency in comparison with a manual tracing method. The proposed system provides a sequential procedure consisting of (1) liver segmentation, (2) blood vessel segmentation, and (3) virtual liver resection for liver graft volumetry. Automatic segmentation algorithms using histogram analysis, hybrid level-set methods, and a customized region growing method were developed. User-friendly interfaces such as sequential and hierarchical user menus, context-sensitive on-screen hotkey menus, and real-time sound and visual feedback were implemented. Blood vessels were excluded from the liver for accurate liver graft volumetry. A large sphere-based interactive method was developed for dividing the liver into left and right lobes with a customized cutting plane. The proposed system was evaluated using 50 CT datasets in terms of graft weight estimation accuracy and task completion time through comparison to the manual tracing method. The accuracy of liver graft weight estimation was assessed by absolute difference (AD) and percentage of AD (%AD) between preoperatively estimated graft weight and intraoperatively measured graft weight. Intra- and inter-observer agreements of liver graft weight estimation were assessed by intraclass correlation coefficients (ICCs) using ten cases randomly selected. The proposed system showed significantly higher accuracy and efficiency in liver graft weight estimation (AD = 21.0 ± 18.4 g; %AD = 3.1% ± 2.8%; percentage of %AD > 10% = none; task completion time = 7.3 ± 1.4 min) than the manual tracing method (AD = 70.5 ± 52.1 g; %AD = 10.2% ± 7.5%; percentage of %AD > 10% = 46%; task completion time = 37.9 ± 7.0 min). The proposed system showed slightly higher intra- and inter-observer agreements (ICC = 0.996 to 0.998) than the manual tracing method (ICC = 0.979 to 0.999). The proposed system was proved accurate and efficient in liver graft volumetry for preoperative planning of LDLT. Copyright © 2018 Elsevier B.V. All rights reserved.

Highly automatic quantification of myocardial oedema in patients with acute myocardial infarction using bright blood T2-weighted CMR

PubMed Central

2013-01-01

Background T2-weighted cardiovascular magnetic resonance (CMR) is clinically-useful for imaging the ischemic area-at-risk and amount of salvageable myocardium in patients with acute myocardial infarction (MI). However, to date, quantification of oedema is user-defined and potentially subjective. Methods We describe a highly automatic framework for quantifying myocardial oedema from bright blood T2-weighted CMR in patients with acute MI. Our approach retains user input (i.e. clinical judgment) to confirm the presence of oedema on an image which is then subjected to an automatic analysis. The new method was tested on 25 consecutive acute MI patients who had a CMR within 48 hours of hospital admission. Left ventricular wall boundaries were delineated automatically by variational level set methods followed by automatic detection of myocardial oedema by fitting a Rayleigh-Gaussian mixture statistical model. These data were compared with results from manual segmentation of the left ventricular wall and oedema, the current standard approach. Results The mean perpendicular distances between automatically detected left ventricular boundaries and corresponding manual delineated boundaries were in the range of 1-2 mm. Dice similarity coefficients for agreement (0=no agreement, 1=perfect agreement) between manual delineation and automatic segmentation of the left ventricular wall boundaries and oedema regions were 0.86 and 0.74, respectively. Conclusion Compared to standard manual approaches, the new highly automatic method for estimating myocardial oedema is accurate and straightforward. It has potential as a generic software tool for physicians to use in clinical practice. PMID:23548176

Automatic Neural Processing of Disorder-Related Stimuli in Social Anxiety Disorder: Faces and More

PubMed Central

Schulz, Claudia; Mothes-Lasch, Martin; Straube, Thomas

2013-01-01

It has been proposed that social anxiety disorder (SAD) is associated with automatic information processing biases resulting in hypersensitivity to signals of social threat such as negative facial expressions. However, the nature and extent of automatic processes in SAD on the behavioral and neural level is not entirely clear yet. The present review summarizes neuroscientific findings on automatic processing of facial threat but also other disorder-related stimuli such as emotional prosody or negative words in SAD. We review initial evidence for automatic activation of the amygdala, insula, and sensory cortices as well as for automatic early electrophysiological components. However, findings vary depending on tasks, stimuli, and neuroscientific methods. Only few studies set out to examine automatic neural processes directly and systematic attempts are as yet lacking. We suggest that future studies should: (1) use different stimulus modalities, (2) examine different emotional expressions, (3) compare findings in SAD with other anxiety disorders, (4) use more sophisticated experimental designs to investigate features of automaticity systematically, and (5) combine different neuroscientific methods (such as functional neuroimaging and electrophysiology). Finally, the understanding of neural automatic processes could also provide hints for therapeutic approaches. PMID:23745116

TU-H-CAMPUS-JeP1-02: Fully Automatic Verification of Automatically Contoured Normal Tissues in the Head and Neck

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCarroll, R; UT Health Science Center, Graduate School of Biomedical Sciences, Houston, TX; Beadle, B

Purpose: To investigate and validate the use of an independent deformable-based contouring algorithm for automatic verification of auto-contoured structures in the head and neck towards fully automated treatment planning. Methods: Two independent automatic contouring algorithms [(1) Eclipse’s Smart Segmentation followed by pixel-wise majority voting, (2) an in-house multi-atlas based method] were used to create contours of 6 normal structures of 10 head-and-neck patients. After rating by a radiation oncologist, the higher performing algorithm was selected as the primary contouring method, the other used for automatic verification of the primary. To determine the ability of the verification algorithm to detect incorrectmore » contours, contours from the primary method were shifted from 0.5 to 2cm. Using a logit model the structure-specific minimum detectable shift was identified. The models were then applied to a set of twenty different patients and the sensitivity and specificity of the models verified. Results: Per physician rating, the multi-atlas method (4.8/5 point scale, with 3 rated as generally acceptable for planning purposes) was selected as primary and the Eclipse-based method (3.5/5) for verification. Mean distance to agreement and true positive rate were selected as covariates in an optimized logit model. These models, when applied to a group of twenty different patients, indicated that shifts could be detected at 0.5cm (brain), 0.75cm (mandible, cord), 1cm (brainstem, cochlea), or 1.25cm (parotid), with sensitivity and specificity greater than 0.95. If sensitivity and specificity constraints are reduced to 0.9, detectable shifts of mandible and brainstem were reduced by 0.25cm. These shifts represent additional safety margins which might be considered if auto-contours are used for automatic treatment planning without physician review. Conclusion: Automatically contoured structures can be automatically verified. This fully automated process could be used to flag auto-contours for special review or used with safety margins in a fully automatic treatment planning system.« less

Data-driven management using quantitative metric and automatic auditing program (QMAP) improves consistency of radiation oncology processes.

PubMed

Yu, Naichang; Xia, Ping; Mastroianni, Anthony; Kolar, Matthew D; Chao, Samuel T; Greskovich, John F; Suh, John H

Process consistency in planning and delivery of radiation therapy is essential to maintain patient safety and treatment quality and efficiency. Ensuring the timely completion of each critical clinical task is one aspect of process consistency. The purpose of this work is to report our experience in implementing a quantitative metric and automatic auditing program (QMAP) with a goal of improving the timely completion of critical clinical tasks. Based on our clinical electronic medical records system, we developed a software program to automatically capture the completion timestamp of each critical clinical task while providing frequent alerts of potential delinquency. These alerts were directed to designated triage teams within a time window that would offer an opportunity to mitigate the potential for late completion. Since July 2011, 18 metrics were introduced in our clinical workflow. We compared the delinquency rates for 4 selected metrics before the implementation of the metric with the delinquency rate of 2016. One-tailed Student t test was used for statistical analysis RESULTS: With an average of 150 daily patients on treatment at our main campus, the late treatment plan completion rate and late weekly physics check were reduced from 18.2% and 8.9% in 2011 to 4.2% and 0.1% in 2016, respectively (P < .01). The late weekly on-treatment physician visit rate was reduced from 7.2% in 2012 to <1.6% in 2016. The yearly late cone beam computed tomography review rate was reduced from 1.6% in 2011 to <0.1% in 2016. QMAP is effective in reducing late completions of critical tasks, which can positively impact treatment quality and patient safety by reducing the potential for errors resulting from distractions, interruptions, and rush in completion of critical tasks. Copyright © 2016 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

A content-based news video retrieval system: NVRS

NASA Astrophysics Data System (ADS)

Liu, Huayong; He, Tingting

2009-10-01

This paper focus on TV news programs and design a content-based news video browsing and retrieval system, NVRS, which is convenient for users to fast browsing and retrieving news video by different categories such as political, finance, amusement, etc. Combining audiovisual features and caption text information, the system automatically segments a complete news program into separate news stories. NVRS supports keyword-based news story retrieval, category-based news story browsing and generates key-frame-based video abstract for each story. Experiments show that the method of story segmentation is effective and the retrieval is also efficient.

Algorithm for Automatic Segmentation of Nuclear Boundaries in Cancer Cells in Three-Channel Luminescent Images

NASA Astrophysics Data System (ADS)

Lisitsa, Y. V.; Yatskou, M. M.; Apanasovich, V. V.; Apanasovich, T. V.

2015-09-01

We have developed an algorithm for segmentation of cancer cell nuclei in three-channel luminescent images of microbiological specimens. The algorithm is based on using a correlation between fluorescence signals in the detection channels for object segmentation, which permits complete automation of the data analysis procedure. We have carried out a comparative analysis of the proposed method and conventional algorithms implemented in the CellProfiler and ImageJ software packages. Our algorithm has an object localization uncertainty which is 2-3 times smaller than for the conventional algorithms, with comparable segmentation accuracy.

One-click scanning of large-size documents using mobile phone camera

NASA Astrophysics Data System (ADS)

Liu, Sijiang; Jiang, Bo; Yang, Yuanjie

2016-07-01

Currently mobile apps for document scanning do not provide convenient operations to tackle large-size documents. In this paper, we present a one-click scanning approach for large-size documents using mobile phone camera. After capturing a continuous video of documents, our approach automatically extracts several key frames by optical flow analysis. Then based on key frames, a mobile GPU based image stitching method is adopted to generate a completed document image with high details. There are no extra manual intervention in the process and experimental results show that our app performs well, showing convenience and practicability for daily life.

Automatic quality assessment and peak identification of auditory brainstem responses with fitted parametric peaks.

PubMed

Valderrama, Joaquin T; de la Torre, Angel; Alvarez, Isaac; Segura, Jose Carlos; Thornton, A Roger D; Sainz, Manuel; Vargas, Jose Luis

2014-05-01

The recording of the auditory brainstem response (ABR) is used worldwide for hearing screening purposes. In this process, a precise estimation of the most relevant components is essential for an accurate interpretation of these signals. This evaluation is usually carried out subjectively by an audiologist. However, the use of automatic methods for this purpose is being encouraged nowadays in order to reduce human evaluation biases and ensure uniformity among test conditions, patients, and screening personnel. This article describes a new method that performs automatic quality assessment and identification of the peaks, the fitted parametric peaks (FPP). This method is based on the use of synthesized peaks that are adjusted to the ABR response. The FPP is validated, on one hand, by an analysis of amplitudes and latencies measured manually by an audiologist and automatically by the FPP method in ABR signals recorded at different stimulation rates; and on the other hand, contrasting the performance of the FPP method with the automatic evaluation techniques based on the correlation coefficient, FSP, and cross correlation with a predefined template waveform by comparing the automatic evaluations of the quality of these methods with subjective evaluations provided by five experienced evaluators on a set of ABR signals of different quality. The results of this study suggest (a) that the FPP method can be used to provide an accurate parameterization of the peaks in terms of amplitude, latency, and width, and (b) that the FPP remains as the method that best approaches the averaged subjective quality evaluation, as well as provides the best results in terms of sensitivity and specificity in ABR signals validation. The significance of these findings and the clinical value of the FPP method are highlighted on this paper. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Semi-automatic tracking, smoothing and segmentation of hyoid bone motion from videofluoroscopic swallowing study.

PubMed

Kim, Won-Seok; Zeng, Pengcheng; Shi, Jian Qing; Lee, Youngjo; Paik, Nam-Jong

2017-01-01

Motion analysis of the hyoid bone via videofluoroscopic study has been used in clinical research, but the classical manual tracking method is generally labor intensive and time consuming. Although some automatic tracking methods have been developed, masked points could not be tracked and smoothing and segmentation, which are necessary for functional motion analysis prior to registration, were not provided by the previous software. We developed software to track the hyoid bone motion semi-automatically. It works even in the situation where the hyoid bone is masked by the mandible and has been validated in dysphagia patients with stroke. In addition, we added the function of semi-automatic smoothing and segmentation. A total of 30 patients' data were used to develop the software, and data collected from 17 patients were used for validation, of which the trajectories of 8 patients were partly masked. Pearson correlation coefficients between the manual and automatic tracking are high and statistically significant (0.942 to 0.991, P-value<0.0001). Relative errors between automatic tracking and manual tracking in terms of the x-axis, y-axis and 2D range of hyoid bone excursion range from 3.3% to 9.2%. We also developed an automatic method to segment each hyoid bone trajectory into four phases (elevation phase, anterior movement phase, descending phase and returning phase). The semi-automatic hyoid bone tracking from VFSS data by our software is valid compared to the conventional manual tracking method. In addition, the ability of automatic indication to switch the automatic mode to manual mode in extreme cases and calibration without attaching the radiopaque object is convenient and useful for users. Semi-automatic smoothing and segmentation provide further information for functional motion analysis which is beneficial to further statistical analysis such as functional classification and prognostication for dysphagia. Therefore, this software could provide the researchers in the field of dysphagia with a convenient, useful, and all-in-one platform for analyzing the hyoid bone motion. Further development of our method to track the other swallowing related structures or objects such as epiglottis and bolus and to carry out the 2D curve registration may be needed for a more comprehensive functional data analysis for dysphagia with big data.

Semi-automatic knee cartilage segmentation

NASA Astrophysics Data System (ADS)

Dam, Erik B.; Folkesson, Jenny; Pettersen, Paola C.; Christiansen, Claus

2006-03-01

Osteo-Arthritis (OA) is a very common age-related cause of pain and reduced range of motion. A central effect of OA is wear-down of the articular cartilage that otherwise ensures smooth joint motion. Quantification of the cartilage breakdown is central in monitoring disease progression and therefore cartilage segmentation is required. Recent advances allow automatic cartilage segmentation with high accuracy in most cases. However, the automatic methods still fail in some problematic cases. For clinical studies, even if a few failing cases will be averaged out in the overall results, this reduces the mean accuracy and precision and thereby necessitates larger/longer studies. Since the severe OA cases are often most problematic for the automatic methods, there is even a risk that the quantification will introduce a bias in the results. Therefore, interactive inspection and correction of these problematic cases is desirable. For diagnosis on individuals, this is even more crucial since the diagnosis will otherwise simply fail. We introduce and evaluate a semi-automatic cartilage segmentation method combining an automatic pre-segmentation with an interactive step that allows inspection and correction. The automatic step consists of voxel classification based on supervised learning. The interactive step combines a watershed transformation of the original scan with the posterior probability map from the classification step at sub-voxel precision. We evaluate the method for the task of segmenting the tibial cartilage sheet from low-field magnetic resonance imaging (MRI) of knees. The evaluation shows that the combined method allows accurate and highly reproducible correction of the segmentation of even the worst cases in approximately ten minutes of interaction.

Automatic Matching of Large Scale Images and Terrestrial LIDAR Based on App Synergy of Mobile Phone

NASA Astrophysics Data System (ADS)

Xia, G.; Hu, C.

2018-04-01

The digitalization of Cultural Heritage based on ground laser scanning technology has been widely applied. High-precision scanning and high-resolution photography of cultural relics are the main methods of data acquisition. The reconstruction with the complete point cloud and high-resolution image requires the matching of image and point cloud, the acquisition of the homonym feature points, the data registration, etc. However, the one-to-one correspondence between image and corresponding point cloud depends on inefficient manual search. The effective classify and management of a large number of image and the matching of large image and corresponding point cloud will be the focus of the research. In this paper, we propose automatic matching of large scale images and terrestrial LiDAR based on APP synergy of mobile phone. Firstly, we develop an APP based on Android, take pictures and record related information of classification. Secondly, all the images are automatically grouped with the recorded information. Thirdly, the matching algorithm is used to match the global and local image. According to the one-to-one correspondence between the global image and the point cloud reflection intensity image, the automatic matching of the image and its corresponding laser radar point cloud is realized. Finally, the mapping relationship between global image, local image and intensity image is established according to homonym feature point. So we can establish the data structure of the global image, the local image in the global image, the local image corresponding point cloud, and carry on the visualization management and query of image.

Design of efficient and simple interface testing equipment for opto-electric tracking system

NASA Astrophysics Data System (ADS)

Liu, Qiong; Deng, Chao; Tian, Jing; Mao, Yao

2016-10-01

Interface testing for opto-electric tracking system is one important work to assure system running performance, aiming to verify the design result of every electronic interface matching the communication protocols or not, by different levels. Opto-electric tracking system nowadays is more complicated, composed of many functional units. Usually, interface testing is executed between units manufactured completely, highly depending on unit design and manufacture progress as well as relative people. As a result, it always takes days or weeks, inefficiently. To solve the problem, this paper promotes an efficient and simple interface testing equipment for opto-electric tracking system, consisting of optional interface circuit card, processor and test program. The hardware cards provide matched hardware interface(s), easily offered from hardware engineer. Automatic code generation technique is imported, providing adaption to new communication protocols. Automatic acquiring items, automatic constructing code architecture and automatic encoding are used to form a new program quickly with adaption. After simple steps, a standard customized new interface testing equipment with matching test program and interface(s) is ready for a waiting-test system in minutes. The efficient and simple interface testing equipment for opto-electric tracking system has worked for many opto-electric tracking system to test entire or part interfaces, reducing test time from days to hours, greatly improving test efficiency, with high software quality and stability, without manual coding. Used as a common tool, the efficient and simple interface testing equipment for opto-electric tracking system promoted by this paper has changed traditional interface testing method and created much higher efficiency.

Direct-method SAD phasing with partial-structure iteration: towards automation.

PubMed

Wang, J W; Chen, J R; Gu, Y X; Zheng, C D; Fan, H F

2004-11-01

The probability formula of direct-method SAD (single-wavelength anomalous diffraction) phasing proposed by Fan & Gu (1985, Acta Cryst. A41, 280-284) contains partial-structure information in the form of a Sim-weighting term. Previously, only the substructure of anomalous scatterers has been included in this term. In the case that the subsequent density modification and model building yields only structure fragments, which do not straightforwardly lead to the complete solution, the partial structure can be fed back into the Sim-weighting term of the probability formula in order to strengthen its phasing power and to benefit the subsequent automatic model building. The procedure has been tested with experimental SAD data from two known proteins with copper and sulfur as the anomalous scatterers.

Integrated circuit test-port architecture and method and apparatus of test-port generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teifel, John

A method and apparatus are provided for generating RTL code for a test-port interface of an integrated circuit. In an embodiment, a test-port table is provided as input data. A computer automatically parses the test-port table into data structures and analyzes it to determine input, output, local, and output-enable port names. The computer generates address-detect and test-enable logic constructed from combinational functions. The computer generates one-hot multiplexer logic for at least some of the output ports. The one-hot multiplexer logic for each port is generated so as to enable the port to toggle between data signals and test signals. Themore » computer then completes the generation of the RTL code.« less

Automatic Registration of GF4 Pms: a High Resolution Multi-Spectral Sensor on Board a Satellite on Geostationary Orbit

NASA Astrophysics Data System (ADS)

Gao, M.; Li, J.

2018-04-01

Geometric correction is an important preprocessing process in the application of GF4 PMS image. The method of geometric correction that is based on the manual selection of geometric control points is time-consuming and laborious. The more common method, based on a reference image, is automatic image registration. This method involves several steps and parameters. For the multi-spectral sensor GF4 PMS, it is necessary for us to identify the best combination of parameters and steps. This study mainly focuses on the following issues: necessity of Rational Polynomial Coefficients (RPC) correction before automatic registration, base band in the automatic registration and configuration of GF4 PMS spatial resolution.

Seamless presentation capture, indexing, and management

NASA Astrophysics Data System (ADS)

Hilbert, David M.; Cooper, Matthew; Denoue, Laurent; Adcock, John; Billsus, Daniel

2005-10-01

Technology abounds for capturing presentations. However, no simple solution exists that is completely automatic. ProjectorBox is a "zero user interaction" appliance that automatically captures, indexes, and manages presentation multimedia. It operates continuously to record the RGB information sent from presentation devices, such as a presenter's laptop, to display devices, such as a projector. It seamlessly captures high-resolution slide images, text and audio. It requires no operator, specialized software, or changes to current presentation practice. Automatic media analysis is used to detect presentation content and segment presentations. The analysis substantially enhances the web-based user interface for browsing, searching, and exporting captured presentations. ProjectorBox has been in use for over a year in our corporate conference room, and has been deployed in two universities. Our goal is to develop automatic capture services that address both corporate and educational needs.

Using implicit attitudes of exercise importance to predict explicit exercise dependence symptoms and exercise behaviors

PubMed Central

Forrest, Lauren N.; Smith, April R.; Fussner, Lauren M.; Dodd, Dorian R.; Clerkin, Elise M.

2015-01-01

Objectives ”Fast” (i.e., implicit) processing is relatively automatic; “slow” (i.e., explicit) processing is relatively controlled and can override automatic processing. These different processing types often produce different responses that uniquely predict behaviors. In the present study, we tested if explicit, self-reported symptoms of exercise dependence and an implicit association of exercise as important predicted exercise behaviors and change in problematic exercise attitudes. Design We assessed implicit attitudes of exercise importance and self-reported symptoms of exercise dependence at Time 1. Participants reported daily exercise behaviors for approximately one month, and then completed a Time 2 assessment of self-reported exercise dependence symptoms. Method Undergraduate males and females (Time 1, N = 93; Time 2, N = 74) tracked daily exercise behaviors for one month and completed an Implicit Association Test assessing implicit exercise importance and subscales of the Exercise Dependence Questionnaire (EDQ) assessing exercise dependence symptoms. Results Implicit attitudes of exercise importance and Time 1 EDQ scores predicted Time 2 EDQ scores. Further, implicit exercise importance and Time 1 EDQ scores predicted daily exercise intensity while Time 1 EDQ scores predicted the amount of days exercised. Conclusion Implicit and explicit processing appear to uniquely predict exercise behaviors and attitudes. Given that different implicit and explicit processes may drive certain exercise factors (e.g., intensity and frequency, respectively), these behaviors may contribute to different aspects of exercise dependence. PMID:26195916

Particle tracking velocimetry in three-dimensional flows

NASA Astrophysics Data System (ADS)

Maas, H. G.; Gruen, A.; Papantoniou, D.

1993-07-01

Particle Tracking Velocimetry (PTV) is a well-known technique for the determination of velocity vectors within an observation volume. However, for a long time it has rarely been applied because of the intensive effort necessary to measure coordinates of a large number of flow marker particles in many images. With today's imaging hardware in combination with the methods of digital image processing and digital photogrammetry, however, new possibilities have arisen for the design of completely automatic PTV systems. A powerful 3 D PTV has been developed in a cooperation of the Institute of Geodesy and Photogrammetry with the Institute of Hydromechanics and Water Resources Management at the Swiss Federal Institute of Technology. In this paper hardware components for 3 D PTV systems wil be discussed, and a strict mathematical model of photogrammetric 3 D coordinate determination, taking into account the different refractive indices in the optical path, will be presented. The system described is capable of determining coordinate sets of some 1000 particles in a flow field at a time resolution of 25 datasets per second and almost arbitrary sequence length completely automatically after an initialization by an operator. The strict mathematical modelling of the measurement geometry, together with a thorough calibration of the system provide for a coordinate accuracy of typically 0.06 mm in X, Y and 0.18 mm in Z (depth coordinate) in a volume of 200 × 160 × 50 mm3.

Application of image recognition-based automatic hyphae detection in fungal keratitis.

PubMed

Wu, Xuelian; Tao, Yuan; Qiu, Qingchen; Wu, Xinyi

2018-03-01

The purpose of this study is to evaluate the accuracy of two methods in diagnosis of fungal keratitis, whereby one method is automatic hyphae detection based on images recognition and the other method is corneal smear. We evaluate the sensitivity and specificity of the method in diagnosis of fungal keratitis, which is automatic hyphae detection based on image recognition. We analyze the consistency of clinical symptoms and the density of hyphae, and perform quantification using the method of automatic hyphae detection based on image recognition. In our study, 56 cases with fungal keratitis (just single eye) and 23 cases with bacterial keratitis were included. All cases underwent the routine inspection of slit lamp biomicroscopy, corneal smear examination, microorganism culture and the assessment of in vivo confocal microscopy images before starting medical treatment. Then, we recognize the hyphae images of in vivo confocal microscopy by using automatic hyphae detection based on image recognition to evaluate its sensitivity and specificity and compare with the method of corneal smear. The next step is to use the index of density to assess the severity of infection, and then find the correlation with the patients' clinical symptoms and evaluate consistency between them. The accuracy of this technology was superior to corneal smear examination (p < 0.05). The sensitivity of the technology of automatic hyphae detection of image recognition was 89.29%, and the specificity was 95.65%. The area under the ROC curve was 0.946. The correlation coefficient between the grading of the severity in the fungal keratitis by the automatic hyphae detection based on image recognition and the clinical grading is 0.87. The technology of automatic hyphae detection based on image recognition was with high sensitivity and specificity, able to identify fungal keratitis, which is better than the method of corneal smear examination. This technology has the advantages when compared with the conventional artificial identification of confocal microscope corneal images, of being accurate, stable and does not rely on human expertise. It was the most useful to the medical experts who are not familiar with fungal keratitis. The technology of automatic hyphae detection based on image recognition can quantify the hyphae density and grade this property. Being noninvasive, it can provide an evaluation criterion to fungal keratitis in a timely, accurate, objective and quantitative manner.

Integrated restructurable flight control system demonstration results

NASA Technical Reports Server (NTRS)

Weiss, Jerold L.; Hsu, John Y.

1987-01-01

The purpose of this study was to examine the complementary capabilities of several restructurable flight control system (RFCS) concepts through the integration of these technologies into a complete system. Performance issues were addressed through a re-examination of RFCS functional requirements, and through a qualitative analysis of the design issues that, if properly addressed during integration, will lead to the highest possible degree of fault-tolerant performance. Software developed under previous phases of this contract and under NAS1-18004 was modified and integrated into a complete RFCS subroutine for NASA's B-737 simulation. The integration of these modules involved the development of methods for dealing with the mismatch between the outputs of the failure detection module and the input requirements of the automatic control system redesign module. The performance of this demonstration system was examined through extensive simulation trials.

Shape-based diffeomorphic registration on hippocampal surfaces using Beltrami holomorphic flow.

PubMed

Lui, Lok Ming; Wong, Tsz Wai; Thompson, Paul; Chan, Tony; Gu, Xianfeng; Yau, Shing-Tung

2010-01-01

We develop a new algorithm to automatically register hippocampal (HP) surfaces with complete geometric matching, avoiding the need to manually label landmark features. A good registration depends on a reasonable choice of shape energy that measures the dissimilarity between surfaces. In our work, we first propose a complete shape index using the Beltrami coefficient and curvatures, which measures subtle local differences. The proposed shape energy is zero if and only if two shapes are identical up to a rigid motion. We then seek the best surface registration by minimizing the shape energy. We propose a simple representation of surface diffeomorphisms using Beltrami coefficients, which simplifies the optimization process. We then iteratively minimize the shape energy using the proposed Beltrami Holomorphic flow (BHF) method. Experimental results on 212 HP of normal and diseased (Alzheimer's disease) subjects show our proposed algorithm is effective in registering HP surfaces with complete geometric matching. The proposed shape energy can also capture local shape differences between HP for disease analysis.

[Wearable Automatic External Defibrillators].

PubMed

Luo, Huajie; Luo, Zhangyuan; Jin, Xun; Zhang, Leilei; Wang, Changjin; Zhang, Wenzan; Tu, Quan

2015-11-01

Defibrillation is the most effective method of treating ventricular fibrillation(VF), this paper introduces wearable automatic external defibrillators based on embedded system which includes EGG measurements, bioelectrical impedance measurement, discharge defibrillation module, which can automatic identify VF signal, biphasic exponential waveform defibrillation discharge. After verified by animal tests, the device can realize EGG acquisition and automatic identification. After identifying the ventricular fibrillation signal, it can automatic defibrillate to abort ventricular fibrillation and to realize the cardiac electrical cardioversion.

Automatic segmentation of the prostate on CT images using deep learning and multi-atlas fusion

NASA Astrophysics Data System (ADS)

Ma, Ling; Guo, Rongrong; Zhang, Guoyi; Tade, Funmilayo; Schuster, David M.; Nieh, Peter; Master, Viraj; Fei, Baowei

2017-02-01

Automatic segmentation of the prostate on CT images has many applications in prostate cancer diagnosis and therapy. However, prostate CT image segmentation is challenging because of the low contrast of soft tissue on CT images. In this paper, we propose an automatic segmentation method by combining a deep learning method and multi-atlas refinement. First, instead of segmenting the whole image, we extract the region of interesting (ROI) to delete irrelevant regions. Then, we use the convolutional neural networks (CNN) to learn the deep features for distinguishing the prostate pixels from the non-prostate pixels in order to obtain the preliminary segmentation results. CNN can automatically learn the deep features adapting to the data, which are different from some handcrafted features. Finally, we select some similar atlases to refine the initial segmentation results. The proposed method has been evaluated on a dataset of 92 prostate CT images. Experimental results show that our method achieved a Dice similarity coefficient of 86.80% as compared to the manual segmentation. The deep learning based method can provide a useful tool for automatic segmentation of the prostate on CT images and thus can have a variety of clinical applications.

Automatic detection of articulation disorders in children with cleft lip and palate.

PubMed

Maier, Andreas; Hönig, Florian; Bocklet, Tobias; Nöth, Elmar; Stelzle, Florian; Nkenke, Emeka; Schuster, Maria

2009-11-01

Speech of children with cleft lip and palate (CLP) is sometimes still disordered even after adequate surgical and nonsurgical therapies. Such speech shows complex articulation disorders, which are usually assessed perceptually, consuming time and manpower. Hence, there is a need for an easy to apply and reliable automatic method. To create a reference for an automatic system, speech data of 58 children with CLP were assessed perceptually by experienced speech therapists for characteristic phonetic disorders at the phoneme level. The first part of the article aims to detect such characteristics by a semiautomatic procedure and the second to evaluate a fully automatic, thus simple, procedure. The methods are based on a combination of speech processing algorithms. The semiautomatic method achieves moderate to good agreement (kappa approximately 0.6) for the detection of all phonetic disorders. On a speaker level, significant correlations between the perceptual evaluation and the automatic system of 0.89 are obtained. The fully automatic system yields a correlation on the speaker level of 0.81 to the perceptual evaluation. This correlation is in the range of the inter-rater correlation of the listeners. The automatic speech evaluation is able to detect phonetic disorders at an experts'level without any additional human postprocessing.

2D Automatic body-fitted structured mesh generation using advancing extraction method

USDA-ARS?s Scientific Manuscript database

This paper presents an automatic mesh generation algorithm for body-fitted structured meshes in Computational Fluids Dynamics (CFD) analysis using the Advancing Extraction Method (AEM). The method is applicable to two-dimensional domains with complex geometries, which have the hierarchical tree-like...

2D automatic body-fitted structured mesh generation using advancing extraction method

USDA-ARS?s Scientific Manuscript database

This paper presents an automatic mesh generation algorithm for body-fitted structured meshes in Computational Fluids Dynamics (CFD) analysis using the Advancing Extraction Method (AEM). The method is applicable to two-dimensional domains with complex geometries, which have the hierarchical tree-like...

Initial Experience With Ultra High-Density Mapping of Human Right Atria.

PubMed

Bollmann, Andreas; Hilbert, Sebastian; John, Silke; Kosiuk, Jedrzej; Hindricks, Gerhard

2016-02-01

Recently, an automatic, high-resolution mapping system has been presented to accurately and quickly identify right atrial geometry and activation patterns in animals, but human data are lacking. This study aims to assess the clinical feasibility and accuracy of high-density electroanatomical mapping of various RA arrhythmias. Electroanatomical maps of the RA (35 partial and 24 complete) were created in 23 patients using a novel mini-basket catheter with 64 electrodes and automatic electrogram annotation. Median acquisition time was 6:43 minutes (0:39-23:05 minutes) with shorter times for partial (4.03 ± 4.13 minutes) than for complete maps (9.41 ± 4.92 minutes). During mapping 3,236 (710-16,306) data points were automatically annotated without manual correction. Maps obtained during sinus rhythm created geometry consistent with CT imaging and demonstrated activation originating at the middle to superior crista terminalis, while maps during CS pacing showed right atrial activation beginning at the infero-septal region. Activation patterns were consistent with cavotricuspid isthmus-dependent atrial flutter (n = 4), complex reentry tachycardia (n = 1), or ectopic atrial tachycardia (n = 2). His bundle and fractionated potentials in the slow pathway region were automatically detected in all patients. Ablation of the cavotricuspid isthmus (n = 9), the atrio-ventricular node (n = 2), atrial ectopy (n = 2), and the slow pathway (n = 3) was successfully and safely performed. RA mapping with this automatic high-density mapping system is fast, feasible, and safe. It is possible to reproducibly identify propagation of atrial activation during sinus rhythm, various tachycardias, and also complex reentrant arrhythmias. © 2015 Wiley Periodicals, Inc.

The Influence of Endmember Selection Method in Extracting Impervious Surface from Airborne Hyperspectral Imagery

NASA Astrophysics Data System (ADS)

Wang, J.; Feng, B.

2016-12-01

Impervious surface area (ISA) has long been studied as an important input into moisture flux models. In general, ISA impedes groundwater recharge, increases stormflow/flood frequency, and alters in-stream and riparian habitats. Urban area is recognized as one of the richest ISA environment. Urban ISA mapping assists flood prevention and urban planning. Hyperspectral imagery (HI), for its ability to detect subtle spectral signature, becomes an ideal candidate in urban ISA mapping. To map ISA from HI involves endmember (EM) selection. The high degree of spatial and spectral heterogeneity of urban environment puts great difficulty in this task: a compromise point is needed between the automatic degree and the good representativeness of the method. The study tested one manual and two semi-automatic EM selection strategies. The manual and the first semi-automatic methods have been widely used in EM selection. The second semi-automatic EM selection method is rather new and has been only proposed for moderate spatial resolution satellite. The manual method visually selected the EM candidates from eight landcover types in the original image. The first semi-automatic method chose the EM candidates using a threshold over the pixel purity index (PPI) map. The second semi-automatic method used the triangle shape of the HI scatter plot in the n-Dimension visualizer to identify the V-I-S (vegetation-impervious surface-soil) EM candidates: the pixels locate at the triangle points. The initial EM candidates from the three methods were further refined by three indexes (EM average RMSE, minimum average spectral angle, and count based EM selection) and generated three spectral libraries, which were used to classify the test image. Spectral angle mapper was applied. The accuracy reports for the classification results were generated. The overall accuracy are 85% for the manual method, 81% for the PPI method, and 87% for the V-I-S method. The V-I-S EM selection method performs best in this study. This fact proves the value of V-I-S EM selection method in not only moderate spatial resolution satellite image but also the more and more accessible high spatial resolution airborne image. This semi-automatic EM selection method can be adopted into a wide range of remote sensing images and provide ISA map for hydrology analysis.

Automatic zebrafish heartbeat detection and analysis for zebrafish embryos.

PubMed

Pylatiuk, Christian; Sanchez, Daniela; Mikut, Ralf; Alshut, Rüdiger; Reischl, Markus; Hirth, Sofia; Rottbauer, Wolfgang; Just, Steffen

2014-08-01

A fully automatic detection and analysis method of heartbeats in videos of nonfixed and nonanesthetized zebrafish embryos is presented. This method reduces the manual workload and time needed for preparation and imaging of the zebrafish embryos, as well as for evaluating heartbeat parameters such as frequency, beat-to-beat intervals, and arrhythmicity. The method is validated by a comparison of the results from automatic and manual detection of the heart rates of wild-type zebrafish embryos 36-120 h postfertilization and of embryonic hearts with bradycardia and pauses in the cardiac contraction.

A new method for designing dual foil electron beam forming systems. II. Feasibility of practical implementation of the method

NASA Astrophysics Data System (ADS)

Adrich, Przemysław

2016-05-01

In Part I of this work a new method for designing dual foil electron beam forming systems was introduced. In this method, an optimal configuration of the dual foil system is found by means of a systematic, automatized scan of system performance in function of its parameters. At each point of the scan, Monte Carlo method is used to calculate the off-axis dose profile in water taking into account detailed and complete geometry of the system. The new method, while being computationally intensive, minimizes the involvement of the designer. In this Part II paper, feasibility of practical implementation of the new method is demonstrated. For this, a prototype software tools were developed and applied to solve a real life design problem. It is demonstrated that system optimization can be completed within few hours time using rather moderate computing resources. It is also demonstrated that, perhaps for the first time, the designer can gain deep insight into system behavior, such that the construction can be simultaneously optimized in respect to a number of functional characteristics besides the flatness of the off-axis dose profile. In the presented example, the system is optimized in respect to both, flatness of the off-axis dose profile and the beam transmission. A number of practical issues related to application of the new method as well as its possible extensions are discussed.

On the Automatic Decellularisation of Porcine Aortae: A Repeatability Study Using a Non-Enzymatic Approach.

PubMed

O'Connor Mooney, Rory; Davis, Niall Francis; Hoey, David; Hogan, Lisa; McGloughlin, Timothy M; Walsh, Michael T

2016-01-01

To investigate the repeatability of automatic decellularisation of porcine aortae using a non-enzymatic approach, addressing current limitations associated with other automatic decellularisation processes. Individual porcine aortae (n = 3) were resected and every third segment (n = 4) was allocated to one of three different groups: a control or a manually or automatically decellularised group. Manual and automatic decellularisation was performed using Triton X-100 (2% v/v) and sodium deoxycholate. Protein preservation and the elimination of a galactosyl-α(1,3)galactose (GAL) epitope were measured using immunohistochemistry and protein binding assays. The presence of residual DNA was determined with gel electrophoresis and spectrophotometry. Scaffold integrity was characterised with scanning electron microscopy and uni-axial tensile testing. Manual and automatic results were compared to one another, to control groups and to current gold standards. The results were comparable to those of current gold standard decellularisation techniques. Successful repeatability was achieved, both manually and automatically, with little effect on mechanical characteristics. Complete acellularity was not confirmed in either decellularisation group. Protein preservation was consistent in both the manually and automatically decellularised groups and between each individual aorta. Elimination of GAL was not achieved. Repeatable automatic decellularisation of porcine aortae is feasible using a Triton X-100-sodium deoxycholate protocol. Protein preservation was satisfactory; however, gold standard thresholds for permissible residual DNA levels were not achieved. Future research will focus on addressing this issue by optimisation of the existing protocol for thick tissues. © 2016 S. Karger AG, Basel.

Mitosis Counting in Breast Cancer: Object-Level Interobserver Agreement and Comparison to an Automatic Method

PubMed Central

Veta, Mitko; van Diest, Paul J.; Jiwa, Mehdi; Al-Janabi, Shaimaa; Pluim, Josien P. W.

2016-01-01

Background Tumor proliferation speed, most commonly assessed by counting of mitotic figures in histological slide preparations, is an important biomarker for breast cancer. Although mitosis counting is routinely performed by pathologists, it is a tedious and subjective task with poor reproducibility, particularly among non-experts. Inter- and intraobserver reproducibility of mitosis counting can be improved when a strict protocol is defined and followed. Previous studies have examined only the agreement in terms of the mitotic count or the mitotic activity score. Studies of the observer agreement at the level of individual objects, which can provide more insight into the procedure, have not been performed thus far. Methods The development of automatic mitosis detection methods has received large interest in recent years. Automatic image analysis is viewed as a solution for the problem of subjectivity of mitosis counting by pathologists. In this paper we describe the results from an interobserver agreement study between three human observers and an automatic method, and make two unique contributions. For the first time, we present an analysis of the object-level interobserver agreement on mitosis counting. Furthermore, we train an automatic mitosis detection method that is robust with respect to staining appearance variability and compare it with the performance of expert observers on an “external” dataset, i.e. on histopathology images that originate from pathology labs other than the pathology lab that provided the training data for the automatic method. Results The object-level interobserver study revealed that pathologists often do not agree on individual objects, even if this is not reflected in the mitotic count. The disagreement is larger for objects from smaller size, which suggests that adding a size constraint in the mitosis counting protocol can improve reproducibility. The automatic mitosis detection method can perform mitosis counting in an unbiased way, with substantial agreement with human experts. PMID:27529701

To do it or to let an automatic tool do it? The priority of control over effort.

PubMed

Osiurak, François; Wagner, Clara; Djerbi, Sara; Navarro, Jordan

2013-01-01

The aim of the present study is to provide experimental data relevant to the issue of what leads humans to use automatic tools. Two answers can be offered. The first is that humans strive to minimize physical and/or cognitive effort (principle of least effort). The second is that humans tend to keep their perceived control over the environment (principle of more control). These two factors certainly play a role, but the question raised here is to what do people give priority in situations wherein both manual and automatic actions take the same time - minimizing effort or keeping perceived control? To answer that question, we built four experiments in which participants were confronted with a recurring choice between performing a task manually (physical effort) or in a semi-automatic way (cognitive effort) versus using an automatic tool that completes the task for them (no effort). In this latter condition, participants were required to follow the progression of the automatic tool step by step. Our results showed that participants favored the manual or semi-automatic condition over the automatic condition. However, when they were offered the opportunity to perform recreational tasks in parallel, the shift toward manual condition disappeared. The findings give support to the idea that people give priority to keeping control over minimizing effort.

Effectiveness of sequential automatic-manual home respiratory polygraphy scoring.

PubMed

Masa, Juan F; Corral, Jaime; Pereira, Ricardo; Duran-Cantolla, Joaquin; Cabello, Marta; Hernández-Blasco, Luis; Monasterio, Carmen; Alonso-Fernandez, Alberto; Chiner, Eusebi; Vázquez-Polo, Francisco-José; Montserrat, Jose M

2013-04-01

Automatic home respiratory polygraphy (HRP) scoring functions can potentially confirm the diagnosis of sleep apnoea-hypopnoea syndrome (SAHS) (obviating technician scoring) in a substantial number of patients. The result would have important management and cost implications. The aim of this study was to determine the diagnostic cost-effectiveness of a sequential HRP scoring protocol (automatic and then manual for residual cases) compared with manual HRP scoring, and with in-hospital polysomnography. We included suspected SAHS patients in a multicentre study and assigned them to home and hospital protocols at random. We constructed receiver operating characteristic (ROC) curves for manual and automatic scoring. Diagnostic agreement for several cut-off points was explored and costs for two equally effective alternatives were calculated. Of 366 randomised patients, 348 completed the protocol. Manual scoring produced better ROC curves than automatic scoring. There was no sensitive automatic or subsequent manual HRP apnoea-hypopnoea index (AHI) cut-off point. The specific cut-off points for automatic and subsequent manual HRP scorings (AHI >25 and >20, respectively) had a specificity of 93% for automatic and 94% for manual scorings. The costs of manual protocol were 9% higher than sequential HRP protocol; these were 69% and 64%, respectively, of the cost of the polysomnography. A sequential HRP scoring protocol is a cost-effective alternative to polysomnography, although with limited cost savings compared to HRP manual scoring.

Method to optimize optical switch topology for photonic network-on-chip

NASA Astrophysics Data System (ADS)

Zhou, Ting; Jia, Hao

2018-04-01

In this paper, we propose a method to optimize the optical switch by substituting optical waveguide crossings for optical switching units and an optimizing algorithm to complete the optimization automatically. The functionality of the optical switch remains constant under optimization. With this method, we simplify the topology of optical switch, which means the insertion loss and power consumption of the whole optical switch can be effectively minimized. Simulation result shows that the number of switching units of the optical switch based on Spanke-Benes can be reduced by 16.7%, 20%, 20%, 19% and 17.9% for the scale from 4 × 4 to 8 × 8 respectively. As a proof of concept, the experimental demonstration of an optimized six-port optical switch based on Spanke-Benes structure by means of silicon photonics chip is reported.

The computation of three-dimensional flows using unstructured grids

NASA Technical Reports Server (NTRS)

Morgan, K.; Peraire, J.; Peiro, J.; Hassan, O.

1991-01-01

A general method is described for automatically discretizing, into unstructured assemblies of tetrahedra, the three-dimensional solution domains of complex shape which are of interest in practical computational aerodynamics. An algorithm for the solution of the compressible Euler equations which can be implemented on such general unstructured tetrahedral grids is described. This is an explicit cell-vertex scheme which follows a general Taylor-Galerkin philosophy. The approach is employed to compute a transonic inviscid flow over a standard wing and the results are shown to compare favorably with experimental observations. As a more practical demonstration, the method is then applied to the analysis of inviscid flow over a complete modern fighter configuration. The effect of using mesh adaptivity is illustrated when the method is applied to the solution of high speed flow in an engine inlet.

Bio-robots automatic navigation with electrical reward stimulation.

PubMed

Sun, Chao; Zhang, Xinlu; Zheng, Nenggan; Chen, Weidong; Zheng, Xiaoxiang

2012-01-01

Bio-robots that controlled by outer stimulation through brain computer interface (BCI) suffer from the dependence on realtime guidance of human operators. Current automatic navigation methods for bio-robots focus on the controlling rules to force animals to obey man-made commands, with animals' intelligence ignored. This paper proposes a new method to realize the automatic navigation for bio-robots with electrical micro-stimulation as real-time rewards. Due to the reward-seeking instinct and trial-and-error capability, bio-robot can be steered to keep walking along the right route with rewards and correct its direction spontaneously when rewards are deprived. In navigation experiments, rat-robots learn the controlling methods in short time. The results show that our method simplifies the controlling logic and realizes the automatic navigation for rat-robots successfully. Our work might have significant implication for the further development of bio-robots with hybrid intelligence.

An automatic method for segmentation of fission tracks in epidote crystal photomicrographs

NASA Astrophysics Data System (ADS)

de Siqueira, Alexandre Fioravante; Nakasuga, Wagner Massayuki; Pagamisse, Aylton; Tello Saenz, Carlos Alberto; Job, Aldo Eloizo

2014-08-01

Manual identification of fission tracks has practical problems, such as variation due to observe-observation efficiency. An automatic processing method that could identify fission tracks in a photomicrograph could solve this problem and improve the speed of track counting. However, separation of nontrivial images is one of the most difficult tasks in image processing. Several commercial and free softwares are available, but these softwares are meant to be used in specific images. In this paper, an automatic method based on starlet wavelets is presented in order to separate fission tracks in mineral photomicrographs. Automatization is obtained by the Matthews correlation coefficient, and results are evaluated by precision, recall and accuracy. This technique is an improvement of a method aimed at segmentation of scanning electron microscopy images. This method is applied in photomicrographs of epidote phenocrystals, in which accuracy higher than 89% was obtained in fission track segmentation, even for difficult images. Algorithms corresponding to the proposed method are available for download. Using the method presented here, a user could easily determine fission tracks in photomicrographs of mineral samples.

A Complete System for Automatic Extraction of Left Ventricular Myocardium From CT Images Using Shape Segmentation and Contour Evolution

PubMed Central

Zhu, Liangjia; Gao, Yi; Appia, Vikram; Yezzi, Anthony; Arepalli, Chesnal; Faber, Tracy; Stillman, Arthur; Tannenbaum, Allen

2014-01-01

The left ventricular myocardium plays a key role in the entire circulation system and an automatic delineation of the myocardium is a prerequisite for most of the subsequent functional analysis. In this paper, we present a complete system for an automatic segmentation of the left ventricular myocardium from cardiac computed tomography (CT) images using the shape information from images to be segmented. The system follows a coarse-to-fine strategy by first localizing the left ventricle and then deforming the myocardial surfaces of the left ventricle to refine the segmentation. In particular, the blood pool of a CT image is extracted and represented as a triangulated surface. Then, the left ventricle is localized as a salient component on this surface using geometric and anatomical characteristics. After that, the myocardial surfaces are initialized from the localization result and evolved by applying forces from the image intensities with a constraint based on the initial myocardial surface locations. The proposed framework has been validated on 34-human and 12-pig CT images, and the robustness and accuracy are demonstrated. PMID:24723531

Rules of Engagement: Incomplete and Complete Pronoun Resolution

PubMed Central

Love, Jessica; McKoon, Gail

2011-01-01

Research on shallow processing suggests that readers sometimes encode only a superficial representation of a text, failing to make use of all available information. Greene, McKoon and Ratcliff (1992) extended this work to pronouns, finding evidence that readers sometimes fail to automatically identify referents even when they are unambiguous. In this paper we revisit those findings. In 11 recognition probe, priming, and self-report experiments, we manipulated Greene et al.’s stories to discover under what circumstances a pronoun’s referent is automatically understood. We lengthened the stories from four to eight lines, a simple manipulation that led to automatic and correct resolution, which we attribute to readers’ increased engagement with the stories. We found evidence of resolution even when the additional text did not mention the pronoun’s referent. In addition, our results suggest that the pronoun temporarily boosts the referent’s accessibility, an advantage that disappears by the end of the next sentence. Finally, we present evidence from memory experiments that support complete pronoun resolution for the longer, but not the shorter, stories. PMID:21480757

Automatic single questionnaire intensity (SQI, EMS98 scale) estimation using ranking models built on the existing BCSF database

NASA Astrophysics Data System (ADS)

Schlupp, A.; Sira, C.; Schmitt, K.; Schaming, M.

2013-12-01

In charge of intensity estimations in France, BCSF has collected and manually analyzed more than 47000 online individual macroseismic questionnaires since 2000 up to intensity VI. These macroseismic data allow us to estimate one SQI value (Single Questionnaire Intensity) for each form following the EMS98 scale. The reliability of the automatic intensity estimation is important as they are today used for automatic shakemaps communications and crisis management. Today, the automatic intensity estimation at BCSF is based on the direct use of thumbnails selected on a menu by the witnesses. Each thumbnail corresponds to an EMS-98 intensity value, allowing us to quickly issue an intensity map of the communal intensity by averaging the SQIs at each city. Afterwards an expert, to determine a definitive SQI, manually analyzes each form. This work is time consuming and not anymore suitable considering the increasing number of testimonies at BCSF. Nevertheless, it can take into account incoherent answers. We tested several automatic methods (USGS algorithm, Correlation coefficient, Thumbnails) (Sira et al. 2013, IASPEI) and compared them with 'expert' SQIs. These methods gave us medium score (between 50 to 60% of well SQI determined and 35 to 40% with plus one or minus one intensity degree). The best fit was observed with the thumbnails. Here, we present new approaches based on 3 statistical ranking methods as 1) Multinomial logistic regression model, 2) Discriminant analysis DISQUAL and 3) Support vector machines (SVMs). The two first methods are standard methods, while the third one is more recent. Theses methods could be applied because the BCSF has already in his database more then 47000 forms and because their questions and answers are well adapted for a statistical analysis. The ranking models could then be used as automatic method constrained on expert analysis. The performance of the automatic methods and the reliability of the estimated SQI can be evaluated thanks to the fact that each definitive BCSF SQIs is determined by an expert analysis. We compare the SQIs obtained by these methods from our database and discuss the coherency and variations between automatic and manual processes. These methods lead to high scores with up to 85% of the forms well classified and most of the remaining forms classified with only a shift of one intensity degree. This allows us to use the ranking methods as the best automatic methods to fast SQIs estimation and to produce fast shakemaps. The next step, to improve the use of these methods, will be to identify explanations for the forms not classified at the correct value and a way to select the few remaining forms that should be analyzed by the expert. Note that beyond intensity VI, on-line questionnaires are insufficient and a field survey is indispensable to estimate intensity. For such survey, in France, BCSF leads a macroseismic intervention group (GIM).

Automatic calibration method for plenoptic camera

NASA Astrophysics Data System (ADS)

Luan, Yinsen; He, Xing; Xu, Bing; Yang, Ping; Tang, Guomao

2016-04-01

An automatic calibration method is proposed for a microlens-based plenoptic camera. First, all microlens images on the white image are searched and recognized automatically based on digital morphology. Then, the center points of microlens images are rearranged according to their relative position relationships. Consequently, the microlens images are located, i.e., the plenoptic camera is calibrated without the prior knowledge of camera parameters. Furthermore, this method is appropriate for all types of microlens-based plenoptic cameras, even the multifocus plenoptic camera, the plenoptic camera with arbitrarily arranged microlenses, or the plenoptic camera with different sizes of microlenses. Finally, we verify our method by the raw data of Lytro. The experiments show that our method has higher intelligence than the methods published before.

Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information.

PubMed

Zhang, Chi; Tong, Li; Zeng, Ying; Jiang, Jingfang; Bu, Haibing; Yan, Bin; Li, Jianxin

2015-01-01

Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an automatic online artifact removal method based on a priori artifact information. The combination of discrete wavelet transform and independent component analysis (ICA), wavelet-ICA, was utilized to separate artifact components. The artifact components were then automatically identified using a priori artifact information, which was acquired in advance. Subsequently, signal reconstruction without artifact components was performed to obtain artifact-free signals. The results showed that, using this automatic online artifact removal method, there were statistical significant improvements of the classification accuracies in both two experiments, namely, motor imagery and emotion recognition.

Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information

PubMed Central

Zhang, Chi; Tong, Li; Zeng, Ying; Jiang, Jingfang; Bu, Haibing; Li, Jianxin

2015-01-01

Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an automatic online artifact removal method based on a priori artifact information. The combination of discrete wavelet transform and independent component analysis (ICA), wavelet-ICA, was utilized to separate artifact components. The artifact components were then automatically identified using a priori artifact information, which was acquired in advance. Subsequently, signal reconstruction without artifact components was performed to obtain artifact-free signals. The results showed that, using this automatic online artifact removal method, there were statistical significant improvements of the classification accuracies in both two experiments, namely, motor imagery and emotion recognition. PMID:26380294

Continuous Video Modeling to Prompt Completion of Multi-Component Tasks by Adults with Moderate Intellectual Disability

ERIC Educational Resources Information Center

Mechling, Linda C.; Ayres, Kevin M.; Purrazzella, Kaitlin; Purrazzella, Kimberly

2014-01-01

This investigation examined the ability of four adults with moderate intellectual disability to complete multi-component tasks using continuous video modeling. Continuous video modeling, which is a newly researched application of video modeling, presents video in a "looping" format which automatically repeats playing of the video while…

AISLE: an automatic volumetric segmentation method for the study of lung allometry.

PubMed

Ren, Hongliang; Kazanzides, Peter

2011-01-01

We developed a fully automatic segmentation method for volumetric CT (computer tomography) datasets to support construction of a statistical atlas for the study of allometric laws of the lung. The proposed segmentation method, AISLE (Automated ITK-Snap based on Level-set), is based on the level-set implementation from an existing semi-automatic segmentation program, ITK-Snap. AISLE can segment the lung field without human interaction and provide intermediate graphical results as desired. The preliminary experimental results show that the proposed method can achieve accurate segmentation, in terms of volumetric overlap metric, by comparing with the ground-truth segmentation performed by a radiologist.

Comparison of Document Index Graph Using TextRank and HITS Weighting Method in Automatic Text Summarization

NASA Astrophysics Data System (ADS)

Hadyan, Fadhlil; Shaufiah; Arif Bijaksana, Moch.

2017-01-01

Automatic summarization is a system that can help someone to take the core information of a long text instantly. The system can help by summarizing text automatically. there’s Already many summarization systems that have been developed at this time but there are still many problems in those system. In this final task proposed summarization method using document index graph. This method utilizes the PageRank and HITS formula used to assess the web page, adapted to make an assessment of words in the sentences in a text document. The expected outcome of this final task is a system that can do summarization of a single document, by utilizing document index graph with TextRank and HITS to improve the quality of the summary results automatically.

CONTINUOUS, AUTOMATED AND SIMULTANEOUS MEASUREMENT OF OXYGEN UPTAKE AND CARBON DIOXIDE EVOLUTION IN BIOLOGICAL SYSTEMS

EPA Science Inventory

Commercial respirometers are capable of continuously and automatically measuring oxygen uptake in bioreactors. A method for continuously and automatically measuring carbon dioxide evolution can be retrofitted to commercial respirometers. Continuous and automatic measurements of...

Automatic allograft bone selection through band registration and its application to distal femur.

PubMed

Zhang, Yu; Qiu, Lei; Li, Fengzan; Zhang, Qing; Zhang, Li; Niu, Xiaohui

2017-09-01

Clinical reports suggest that large bone defects could be effectively restored by allograft bone transplantation, where allograft bone selection acts an important role. Besides, there is a huge demand for developing the automatic allograft bone selection methods, as the automatic methods could greatly improve the management efficiency of the large bone banks. Although several automatic methods have been presented to select the most suitable allograft bone from the massive allograft bone bank, these methods still suffer from inaccuracy. In this paper, we propose an effective allograft bone selection method without using the contralateral bones. Firstly, the allograft bone is globally aligned to the recipient bone by surface registration. Then, the global alignment is further refined through band registration. The band, defined as the recipient points within the lifted and lowered cutting planes, could involve more local structure of the defected segment. Therefore, our method could achieve robust alignment and high registration accuracy of the allograft and recipient. Moreover, the existing contour method and surface method could be unified into one framework under our method by adjusting the lift and lower distances of the cutting planes. Finally, our method has been validated on the database of distal femurs. The experimental results indicate that our method outperforms the surface method and contour method.

Shaping Attention with Reward: Effects of Reward on Space- and Object-Based Selection

PubMed Central

Shomstein, Sarah; Johnson, Jacoba

2014-01-01

The contribution of rewarded actions to automatic attentional selection remains obscure. We hypothesized that some forms of automatic orienting, such as object-based selection, can be completely abandoned in lieu of reward maximizing strategy. While presenting identical visual stimuli to the observer, in a set of two experiments, we manipulate what is being rewarded (different object targets or random object locations) and the type of reward received (money or points). It was observed that reward alone guides attentional selection, entirely predicting behavior. These results suggest that guidance of selective attention, while automatic, is flexible and can be adjusted in accordance with external non-sensory reward-based factors. PMID:24121412

Comparison of histomorphometrical data obtained with two different image analysis methods.

PubMed

Ballerini, Lucia; Franke-Stenport, Victoria; Borgefors, Gunilla; Johansson, Carina B

2007-08-01

A common way to determine tissue acceptance of biomaterials is to perform histomorphometrical analysis on histologically stained sections from retrieved samples with surrounding tissue, using various methods. The "time and money consuming" methods and techniques used are often "in house standards". We address light microscopic investigations of bone tissue reactions on un-decalcified cut and ground sections of threaded implants. In order to screen sections and generate results faster, the aim of this pilot project was to compare results generated with the in-house standard visual image analysis tool (i.e., quantifications and judgements done by the naked eye) with a custom made automatic image analysis program. The histomorphometrical bone area measurements revealed no significant differences between the methods but the results of the bony contacts varied significantly. The raw results were in relative agreement, i.e., the values from the two methods were proportional to each other: low bony contact values in the visual method corresponded to low values with the automatic method. With similar resolution images and further improvements of the automatic method this difference should become insignificant. A great advantage using the new automatic image analysis method is that it is time saving--analysis time can be significantly reduced.

46 CFR 98.25-35 - Refrigerated systems.

Code of Federal Regulations, 2011 CFR

2011-10-01

... temperature of the liquid below atmospheric, at least two complete refrigeration plants automatically... auxiliaries for proper operation. The capacity of each refrigeration compressor shall be sufficient to...

46 CFR 98.25-35 - Refrigerated systems.

Code of Federal Regulations, 2014 CFR

2014-10-01

... temperature of the liquid below atmospheric, at least two complete refrigeration plants automatically... auxiliaries for proper operation. The capacity of each refrigeration compressor shall be sufficient to...

46 CFR 98.25-35 - Refrigerated systems.

Code of Federal Regulations, 2010 CFR

2010-10-01

... temperature of the liquid below atmospheric, at least two complete refrigeration plants automatically... auxiliaries for proper operation. The capacity of each refrigeration compressor shall be sufficient to...

46 CFR 98.25-35 - Refrigerated systems.

Code of Federal Regulations, 2013 CFR

2013-10-01

... temperature of the liquid below atmospheric, at least two complete refrigeration plants automatically... auxiliaries for proper operation. The capacity of each refrigeration compressor shall be sufficient to...

46 CFR 98.25-35 - Refrigerated systems.

Code of Federal Regulations, 2012 CFR

2012-10-01

... temperature of the liquid below atmospheric, at least two complete refrigeration plants automatically... auxiliaries for proper operation. The capacity of each refrigeration compressor shall be sufficient to...

A fast and automatic mosaic method for high-resolution satellite images

NASA Astrophysics Data System (ADS)

Chen, Hongshun; He, Hui; Xiao, Hongyu; Huang, Jing

2015-12-01

We proposed a fast and fully automatic mosaic method for high-resolution satellite images. First, the overlapped rectangle is computed according to geographical locations of the reference and mosaic images and feature points on both the reference and mosaic images are extracted by a scale-invariant feature transform (SIFT) algorithm only from the overlapped region. Then, the RANSAC method is used to match feature points of both images. Finally, the two images are fused into a seamlessly panoramic image by the simple linear weighted fusion method or other method. The proposed method is implemented in C++ language based on OpenCV and GDAL, and tested by Worldview-2 multispectral images with a spatial resolution of 2 meters. Results show that the proposed method can detect feature points efficiently and mosaic images automatically.

Automatic centring and bonding of lenses

NASA Astrophysics Data System (ADS)

Krey, Stefan; Heinisch, J.; Dumitrescu, E.

2007-05-01

We present an automatic bonding station which is able to center and bond individual lenses or doublets to a barrel with sub micron centring accuracy. The complete manufacturing cycle includes the glue dispensing and UV curing. During the process the state of centring is continuously controlled by the vision software, and the final result is recorded to a file for process statistics. Simple pass or fail results are displayed to the operator at the end of the process.

Initial design and evaluation of automatic restructurable flight control system concepts

NASA Technical Reports Server (NTRS)

Weiss, J. L.; Looze, D. P.; Eterno, J. S.; Grunberg, D. B.

1986-01-01

Results of efforts to develop automatic control design procedures for restructurable aircraft control systems is presented. The restructurable aircraft control problem involves designing a fault tolerance control system which can accommodate a wide variety of unanticipated aircraft failure. Under NASA sponsorship, many of the technologies which make such a system possible were developed and tested. Future work will focus on developing a methodology for integrating these technologies and demonstration of a complete system.

Comparison of manual and automatic techniques for substriatal segmentation in 11C-raclopride high-resolution PET studies.

PubMed

Johansson, Jarkko; Alakurtti, Kati; Joutsa, Juho; Tohka, Jussi; Ruotsalainen, Ulla; Rinne, Juha O

2016-10-01

The striatum is the primary target in regional C-raclopride-PET studies, and despite its small volume, it contains several functional and anatomical subregions. The outcome of the quantitative dopamine receptor study using C-raclopride-PET depends heavily on the quality of the region-of-interest (ROI) definition of these subregions. The aim of this study was to evaluate subregional analysis techniques because new approaches have emerged, but have not yet been compared directly. In this paper, we compared manual ROI delineation with several automatic methods. The automatic methods used either direct clustering of the PET image or individualization of chosen brain atlases on the basis of MRI or PET image normalization. State-of-the-art normalization methods and atlases were applied, including those provided in the FreeSurfer, Statistical Parametric Mapping8, and FSL software packages. Evaluation of the automatic methods was based on voxel-wise congruity with the manual delineations and the test-retest variability and reliability of the outcome measures using data from seven healthy male participants who were scanned twice with C-raclopride-PET on the same day. The results show that both manual and automatic methods can be used to define striatal subregions. Although most of the methods performed well with respect to the test-retest variability and reliability of binding potential, the smallest average test-retest variability and SEM were obtained using a connectivity-based atlas and PET normalization (test-retest variability=4.5%, SEM=0.17). The current state-of-the-art automatic ROI methods can be considered good alternatives for subjective and laborious manual segmentation in C-raclopride-PET studies.

Dissociation between controlled and automatic processes in the behavioral variant of fronto-temporal dementia.

PubMed

Collette, Fabienne; Van der Linden, Martial; Salmon, Eric

2010-01-01

A decline of cognitive functioning affecting several cognitive domains was frequently reported in patients with frontotemporal dementia. We were interested in determining if these deficits can be interpreted as reflecting an impairment of controlled cognitive processes by using an assessment tool specifically developed to explore the distinction between automatic and controlled processes, namely the process dissociation procedure (PDP) developed by Jacoby. The PDP was applied to a word stem completion task to determine the contribution of automatic and controlled processes to episodic memory performance and was administered to a group of 12 patients with the behavioral variant of frontotemporal dementia (bv-FTD) and 20 control subjects (CS). Bv-FTD patients obtained a lower performance than CS for the estimates of controlled processes, but no group differences was observed for estimates of automatic processes. The between-groups comparison of the estimates of controlled and automatic processes showed a larger contribution of automatic processes to performance in bv-FTD, while a slightly more important contribution of controlled processes was observed in control subjects. These results are clearly indicative of an alteration of controlled memory processes in bv-FTD.

The challenge of cerebral magnetic resonance imaging in neonates: A new method using mathematical morphology for the segmentation of structures including diffuse excessive high signal intensities.

PubMed

Xu, Yongchao; Morel, Baptiste; Dahdouh, Sonia; Puybareau, Élodie; Virzì, Alessio; Urien, Héléne; Géraud, Thierry; Adamsbaum, Catherine; Bloch, Isabelle

2018-05-17

Preterm birth is a multifactorial condition associated with increased morbidity and mortality. Diffuse excessive high signal intensity (DEHSI) has been recently described on T2-weighted MR sequences in this population and thought to be associated with neuropathologies. To date, no robust and reproducible method to assess the presence of white matter hyperintensities has been developed, perhaps explaining the current controversy over their prognostic value. The aim of this paper is to propose a new semi-automated framework to detect DEHSI on neonatal brain MR images having a particular pattern due to the physiological lack of complete myelination of the white matter. A novel method for semi- automatic segmentation of neonatal brain structures and DEHSI, based on mathematical morphology and on max-tree representations of the images is thus described. It is a mandatory first step to identify and clinically assess homogeneous cohorts of neonates for DEHSI and/or volume of any other segmented structures. Implemented in a user-friendly interface, the method makes it straightforward to select relevant markers of structures to be segmented, and if needed, apply eventually manual corrections. This method responds to the increasing need for providing medical experts with semi-automatic tools for image analysis, and overcomes the limitations of visual analysis alone, prone to subjectivity and variability. Experimental results demonstrate that the method is accurate, with excellent reproducibility and with very few manual corrections needed. Although the method was intended initially for images acquired at 1.5T, which corresponds to the usual clinical practice, preliminary results on images acquired at 3T suggest that the proposed approach can be generalized. Copyright © 2018 Elsevier B.V. All rights reserved.

Development of an Automatic Differentiation Version of the FPX Rotor Code

NASA Technical Reports Server (NTRS)

Hu, Hong

1996-01-01

The ADIFOR2.0 automatic differentiator is applied to the FPX rotor code along with the grid generator GRGN3. The FPX is an eXtended Full-Potential CFD code for rotor calculations. The automatic differentiation version of the code is obtained, which provides both non-geometry and geometry sensitivity derivatives. The sensitivity derivatives via automatic differentiation are presented and compared with divided difference generated derivatives. The study shows that automatic differentiation method gives accurate derivative values in an efficient manner.

Automatic weld torch guidance control system

NASA Technical Reports Server (NTRS)

Smaith, H. E.; Wall, W. A.; Burns, M. R., Jr.

1982-01-01

A highly reliable, fully digital, closed circuit television optical, type automatic weld seam tracking control system was developed. This automatic tracking equipment is used to reduce weld tooling costs and increase overall automatic welding reliability. The system utilizes a charge injection device digital camera which as 60,512 inidividual pixels as the light sensing elements. Through conventional scanning means, each pixel in the focal plane is sequentially scanned, the light level signal digitized, and an 8-bit word transmitted to scratch pad memory. From memory, the microprocessor performs an analysis of the digital signal and computes the tracking error. Lastly, the corrective signal is transmitted to a cross seam actuator digital drive motor controller to complete the closed loop, feedback, tracking system. This weld seam tracking control system is capable of a tracking accuracy of + or - 0.2 mm, or better. As configured, the system is applicable to square butt, V-groove, and lap joint weldments.

Using suggestion to model different types of automatic writing.

PubMed

Walsh, E; Mehta, M A; Oakley, D A; Guilmette, D N; Gabay, A; Halligan, P W; Deeley, Q

2014-05-01

Our sense of self includes awareness of our thoughts and movements, and our control over them. This feeling can be altered or lost in neuropsychiatric disorders as well as in phenomena such as "automatic writing" whereby writing is attributed to an external source. Here, we employed suggestion in highly hypnotically suggestible participants to model various experiences of automatic writing during a sentence completion task. Results showed that the induction of hypnosis, without additional suggestion, was associated with a small but significant reduction of control, ownership, and awareness for writing. Targeted suggestions produced a double dissociation between thought and movement components of writing, for both feelings of control and ownership, and additionally, reduced awareness of writing. Overall, suggestion produced selective alterations in the control, ownership, and awareness of thought and motor components of writing, thus enabling key aspects of automatic writing, observed across different clinical and cultural settings, to be modelled. Copyright © 2014. Published by Elsevier Inc.

Automatic view synthesis by image-domain-warping.

PubMed

Stefanoski, Nikolce; Wang, Oliver; Lang, Manuel; Greisen, Pierre; Heinzle, Simon; Smolic, Aljosa

2013-09-01

Today, stereoscopic 3D (S3D) cinema is already mainstream, and almost all new display devices for the home support S3D content. S3D distribution infrastructure to the home is already established partly in the form of 3D Blu-ray discs, video on demand services, or television channels. The necessity to wear glasses is, however, often considered as an obstacle, which hinders broader acceptance of this technology in the home. Multiviewautostereoscopic displays enable a glasses free perception of S3D content for several observers simultaneously, and support head motion parallax in a limited range. To support multiviewautostereoscopic displays in an already established S3D distribution infrastructure, a synthesis of new views from S3D video is needed. In this paper, a view synthesis method based on image-domain-warping (IDW) is presented that automatically synthesizes new views directly from S3D video and functions completely. IDW relies on an automatic and robust estimation of sparse disparities and image saliency information, and enforces target disparities in synthesized images using an image warping framework. Two configurations of the view synthesizer in the scope of a transmission and view synthesis framework are analyzed and evaluated. A transmission and view synthesis system that uses IDW is recently submitted to MPEG's call for proposals on 3D video technology, where it is ranked among the four best performing proposals.

Verification of road databases using multiple road models

NASA Astrophysics Data System (ADS)

Ziems, Marcel; Rottensteiner, Franz; Heipke, Christian

2017-08-01

In this paper a new approach for automatic road database verification based on remote sensing images is presented. In contrast to existing methods, the applicability of the new approach is not restricted to specific road types, context areas or geographic regions. This is achieved by combining several state-of-the-art road detection and road verification approaches that work well under different circumstances. Each one serves as an independent module representing a unique road model and a specific processing strategy. All modules provide independent solutions for the verification problem of each road object stored in the database in form of two probability distributions, the first one for the state of a database object (correct or incorrect), and a second one for the state of the underlying road model (applicable or not applicable). In accordance with the Dempster-Shafer Theory, both distributions are mapped to a new state space comprising the classes correct, incorrect and unknown. Statistical reasoning is applied to obtain the optimal state of a road object. A comparison with state-of-the-art road detection approaches using benchmark datasets shows that in general the proposed approach provides results with larger completeness. Additional experiments reveal that based on the proposed method a highly reliable semi-automatic approach for road data base verification can be designed.

Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition

PubMed Central

Vajda, Szilárd; Rangoni, Yves; Cecotti, Hubert

2015-01-01

For training supervised classifiers to recognize different patterns, large data collections with accurate labels are necessary. In this paper, we propose a generic, semi-automatic labeling technique for large handwritten character collections. In order to speed up the creation of a large scale ground truth, the method combines unsupervised clustering and minimal expert knowledge. To exploit the potential discriminant complementarities across features, each character is projected into five different feature spaces. After clustering the images in each feature space, the human expert labels the cluster centers. Each data point inherits the label of its cluster’s center. A majority (or unanimity) vote decides the label of each character image. The amount of human involvement (labeling) is strictly controlled by the number of clusters – produced by the chosen clustering approach. To test the efficiency of the proposed approach, we have compared, and evaluated three state-of-the art clustering methods (k-means, self-organizing maps, and growing neural gas) on the MNIST digit data set, and a Lampung Indonesian character data set, respectively. Considering a k-nn classifier, we show that labeling manually only 1.3% (MNIST), and 3.2% (Lampung) of the training data, provides the same range of performance than a completely labeled data set would. PMID:25870463

Automatic information extraction from unstructured mammography reports using distributed semantics.

PubMed

Gupta, Anupama; Banerjee, Imon; Rubin, Daniel L

2018-02-01

To date, the methods developed for automated extraction of information from radiology reports are mainly rule-based or dictionary-based, and, therefore, require substantial manual effort to build these systems. Recent efforts to develop automated systems for entity detection have been undertaken, but little work has been done to automatically extract relations and their associated named entities in narrative radiology reports that have comparable accuracy to rule-based methods. Our goal is to extract relations in a unsupervised way from radiology reports without specifying prior domain knowledge. We propose a hybrid approach for information extraction that combines dependency-based parse tree with distributed semantics for generating structured information frames about particular findings/abnormalities from the free-text mammography reports. The proposed IE system obtains a F 1 -score of 0.94 in terms of completeness of the content in the information frames, which outperforms a state-of-the-art rule-based system in this domain by a significant margin. The proposed system can be leveraged in a variety of applications, such as decision support and information retrieval, and may also easily scale to other radiology domains, since there is no need to tune the system with hand-crafted information extraction rules. Copyright © 2018 Elsevier Inc. All rights reserved.

DyKOSMap: A framework for mapping adaptation between biomedical knowledge organization systems.

PubMed

Dos Reis, Julio Cesar; Pruski, Cédric; Da Silveira, Marcos; Reynaud-Delaître, Chantal

2015-06-01

Knowledge Organization Systems (KOS) and their associated mappings play a central role in several decision support systems. However, by virtue of knowledge evolution, KOS entities are modified over time, impacting mappings and potentially turning them invalid. This requires semi-automatic methods to maintain such semantic correspondences up-to-date at KOS evolution time. We define a complete and original framework based on formal heuristics that drives the adaptation of KOS mappings. Our approach takes into account the definition of established mappings, the evolution of KOS and the possible changes that can be applied to mappings. This study experimentally evaluates the proposed heuristics and the entire framework on realistic case studies borrowed from the biomedical domain, using official mappings between several biomedical KOSs. We demonstrate the overall performance of the approach over biomedical datasets of different characteristics and sizes. Our findings reveal the effectiveness in terms of precision, recall and F-measure of the suggested heuristics and methods defining the framework to adapt mappings affected by KOS evolution. The obtained results contribute and improve the quality of mappings over time. The proposed framework can adapt mappings largely automatically, facilitating thus the maintenance task. The implemented algorithms and tools support and minimize the work of users in charge of KOS mapping maintenance. Copyright © 2015 Elsevier Inc. All rights reserved.

Color edges extraction using statistical features and automatic threshold technique: application to the breast cancer cells.

PubMed

Ben Chaabane, Salim; Fnaiech, Farhat

2014-01-23

Color image segmentation has been so far applied in many areas; hence, recently many different techniques have been developed and proposed. In the medical imaging area, the image segmentation may be helpful to provide assistance to doctor in order to follow-up the disease of a certain patient from the breast cancer processed images. The main objective of this work is to rebuild and also to enhance each cell from the three component images provided by an input image. Indeed, from an initial segmentation obtained using the statistical features and histogram threshold techniques, the resulting segmentation may represent accurately the non complete and pasted cells and enhance them. This allows real help to doctors, and consequently, these cells become clear and easy to be counted. A novel method for color edges extraction based on statistical features and automatic threshold is presented. The traditional edge detector, based on the first and the second order neighborhood, describing the relationship between the current pixel and its neighbors, is extended to the statistical domain. Hence, color edges in an image are obtained by combining the statistical features and the automatic threshold techniques. Finally, on the obtained color edges with specific primitive color, a combination rule is used to integrate the edge results over the three color components. Breast cancer cell images were used to evaluate the performance of the proposed method both quantitatively and qualitatively. Hence, a visual and a numerical assessment based on the probability of correct classification (PC), the false classification (Pf), and the classification accuracy (Sens(%)) are presented and compared with existing techniques. The proposed method shows its superiority in the detection of points which really belong to the cells, and also the facility of counting the number of the processed cells. Computer simulations highlight that the proposed method substantially enhances the segmented image with smaller error rates better than other existing algorithms under the same settings (patterns and parameters). Moreover, it provides high classification accuracy, reaching the rate of 97.94%. Additionally, the segmentation method may be extended to other medical imaging types having similar properties.

An overview of very high level software design methods

NASA Technical Reports Server (NTRS)

Asdjodi, Maryam; Hooper, James W.

1988-01-01

Very High Level design methods emphasize automatic transfer of requirements to formal design specifications, and/or may concentrate on automatic transformation of formal design specifications that include some semantic information of the system into machine executable form. Very high level design methods range from general domain independent methods to approaches implementable for specific applications or domains. Applying AI techniques, abstract programming methods, domain heuristics, software engineering tools, library-based programming and other methods different approaches for higher level software design are being developed. Though one finds that a given approach does not always fall exactly in any specific class, this paper provides a classification for very high level design methods including examples for each class. These methods are analyzed and compared based on their basic approaches, strengths and feasibility for future expansion toward automatic development of software systems.

Automatic ultrasound image enhancement for 2D semi-automatic breast-lesion segmentation

NASA Astrophysics Data System (ADS)

Lu, Kongkuo; Hall, Christopher S.

2014-03-01

Breast cancer is the fastest growing cancer, accounting for 29%, of new cases in 2012, and second leading cause of cancer death among women in the United States and worldwide. Ultrasound (US) has been used as an indispensable tool for breast cancer detection/diagnosis and treatment. In computer-aided assistance, lesion segmentation is a preliminary but vital step, but the task is quite challenging in US images, due to imaging artifacts that complicate detection and measurement of the suspect lesions. The lesions usually present with poor boundary features and vary significantly in size, shape, and intensity distribution between cases. Automatic methods are highly application dependent while manual tracing methods are extremely time consuming and have a great deal of intra- and inter- observer variability. Semi-automatic approaches are designed to counterbalance the advantage and drawbacks of the automatic and manual methods. However, considerable user interaction might be necessary to ensure reasonable segmentation for a wide range of lesions. This work proposes an automatic enhancement approach to improve the boundary searching ability of the live wire method to reduce necessary user interaction while keeping the segmentation performance. Based on the results of segmentation of 50 2D breast lesions in US images, less user interaction is required to achieve desired accuracy, i.e. < 80%, when auto-enhancement is applied for live-wire segmentation.

Method of center localization for objects containing concentric arcs

NASA Astrophysics Data System (ADS)

Kuznetsova, Elena G.; Shvets, Evgeny A.; Nikolaev, Dmitry P.

2015-02-01

This paper proposes a method for automatic center location of objects containing concentric arcs. The method utilizes structure tensor analysis and voting scheme optimized with Fast Hough Transform. Two applications of the proposed method are considered: (i) wheel tracking in video-based system for automatic vehicle classification and (ii) tree growth rings analysis on a tree cross cut image.

Multi-criteria evaluation methods in the production scheduling

NASA Astrophysics Data System (ADS)

Kalinowski, K.; Krenczyk, D.; Paprocka, I.; Kempa, W.; Grabowik, C.

2016-08-01

The paper presents a discussion on the practical application of different methods of multi-criteria evaluation in the process of scheduling in manufacturing systems. Among the methods two main groups are specified: methods based on the distance function (using metacriterion) and methods that create a Pareto set of possible solutions. The basic criteria used for scheduling were also described. The overall procedure of evaluation process in production scheduling was presented. It takes into account the actions in the whole scheduling process and human decision maker (HDM) participation. The specified HDM decisions are related to creating and editing a set of evaluation criteria, selection of multi-criteria evaluation method, interaction in the searching process, using informal criteria and making final changes in the schedule for implementation. According to need, process scheduling may be completely or partially automated. Full automatization is possible in case of metacriterion based objective function and if Pareto set is selected - the final decision has to be done by HDM.

Automatic Keyword Extraction from Individual Documents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rose, Stuart J.; Engel, David W.; Cramer, Nicholas O.

2010-05-03

This paper introduces a novel and domain-independent method for automatically extracting keywords, as sequences of one or more words, from individual documents. We describe the method’s configuration parameters and algorithm, and present an evaluation on a benchmark corpus of technical abstracts. We also present a method for generating lists of stop words for specific corpora and domains, and evaluate its ability to improve keyword extraction on the benchmark corpus. Finally, we apply our method of automatic keyword extraction to a corpus of news articles and define metrics for characterizing the exclusivity, essentiality, and generality of extracted keywords within a corpus.

Automatic Topography Using High Precision Digital Moire Methods

NASA Astrophysics Data System (ADS)

Yatagai, T.; Idesawa, M.; Saito, S.

1983-07-01

Three types of moire topographic methods using digital techniques are proposed. Deformed gratings obtained by projecting a reference grating onto an object under test are subjected to digital analysis. The electronic analysis procedures of deformed gratings described here enable us to distinguish between depression and elevation of the object, so that automatic measurement of 3-D shapes and automatic moire fringe interpolation are performed. Based on the digital moire methods, we have developed a practical measurement system, with a linear photodiode array on a micro-stage as a scanning image sensor. Examples of fringe analysis in medical applications are presented.

Automatic and manual segmentation of healthy retinas using high-definition optical coherence tomography.

PubMed

Golbaz, Isabelle; Ahlers, Christian; Goesseringer, Nina; Stock, Geraldine; Geitzenauer, Wolfgang; Prünte, Christian; Schmidt-Erfurth, Ursula Margarethe

2011-03-01

This study compared automatic- and manual segmentation modalities in the retina of healthy eyes using high-definition optical coherence tomography (HD-OCT). Twenty retinas in 20 healthy individuals were examined using an HD-OCT system (Carl Zeiss Meditec, Inc.). Three-dimensional imaging was performed with an axial resolution of 6 μm at a maximum scanning speed of 25,000 A-scans/second. Volumes of 6 × 6 × 2 mm were scanned. Scans were analysed using a matlab-based algorithm and a manual segmentation software system (3D-Doctor). The volume values calculated by the two methods were compared. Statistical analysis revealed a high correlation between automatic and manual modes of segmentation. The automatic mode of measuring retinal volume and the corresponding three-dimensional images provided similar results to the manual segmentation procedure. Both methods were able to visualize retinal and subretinal features accurately. This study compared two methods of assessing retinal volume using HD-OCT scans in healthy retinas. Both methods were able to provide realistic volumetric data when applied to raster scan sets. Manual segmentation methods represent an adequate tool with which to control automated processes and to identify clinically relevant structures, whereas automatic procedures will be needed to obtain data in larger patient populations. © 2009 The Authors. Journal compilation © 2009 Acta Ophthalmol.

Mitosis Counting in Breast Cancer: Object-Level Interobserver Agreement and Comparison to an Automatic Method.

PubMed

Veta, Mitko; van Diest, Paul J; Jiwa, Mehdi; Al-Janabi, Shaimaa; Pluim, Josien P W

2016-01-01

Tumor proliferation speed, most commonly assessed by counting of mitotic figures in histological slide preparations, is an important biomarker for breast cancer. Although mitosis counting is routinely performed by pathologists, it is a tedious and subjective task with poor reproducibility, particularly among non-experts. Inter- and intraobserver reproducibility of mitosis counting can be improved when a strict protocol is defined and followed. Previous studies have examined only the agreement in terms of the mitotic count or the mitotic activity score. Studies of the observer agreement at the level of individual objects, which can provide more insight into the procedure, have not been performed thus far. The development of automatic mitosis detection methods has received large interest in recent years. Automatic image analysis is viewed as a solution for the problem of subjectivity of mitosis counting by pathologists. In this paper we describe the results from an interobserver agreement study between three human observers and an automatic method, and make two unique contributions. For the first time, we present an analysis of the object-level interobserver agreement on mitosis counting. Furthermore, we train an automatic mitosis detection method that is robust with respect to staining appearance variability and compare it with the performance of expert observers on an "external" dataset, i.e. on histopathology images that originate from pathology labs other than the pathology lab that provided the training data for the automatic method. The object-level interobserver study revealed that pathologists often do not agree on individual objects, even if this is not reflected in the mitotic count. The disagreement is larger for objects from smaller size, which suggests that adding a size constraint in the mitosis counting protocol can improve reproducibility. The automatic mitosis detection method can perform mitosis counting in an unbiased way, with substantial agreement with human experts.

ARES v2: new features and improved performance

NASA Astrophysics Data System (ADS)

Sousa, S. G.; Santos, N. C.; Adibekyan, V.; Delgado-Mena, E.; Israelian, G.

2015-05-01

Aims: We present a new upgraded version of ARES. The new version includes a series of interesting new features such as automatic radial velocity correction, a fully automatic continuum determination, and an estimation of the errors for the equivalent widths. Methods: The automatic correction of the radial velocity is achieved with a simple cross-correlation function, and the automatic continuum determination, as well as the estimation of the errors, relies on a new approach to evaluating the spectral noise at the continuum level. Results: ARES v2 is totally compatible with its predecessor. We show that the fully automatic continuum determination is consistent with the previous methods applied for this task. It also presents a significant improvement on its performance thanks to the implementation of a parallel computation using the OpenMP library. Automatic Routine for line Equivalent widths in stellar Spectra - ARES webpage: http://www.astro.up.pt/~sousasag/ares/Based on observations made with ESO Telescopes at the La Silla Paranal Observatory under programme ID 075.D-0800(A).

Automated segmentation of myocardial scar in late enhancement MRI using combined intensity and spatial information.

PubMed

Tao, Qian; Milles, Julien; Zeppenfeld, Katja; Lamb, Hildo J; Bax, Jeroen J; Reiber, Johan H C; van der Geest, Rob J

2010-08-01

Accurate assessment of the size and distribution of a myocardial infarction (MI) from late gadolinium enhancement (LGE) MRI is of significant prognostic value for postinfarction patients. In this paper, an automatic MI identification method combining both intensity and spatial information is presented in a clear framework of (i) initialization, (ii) false acceptance removal, and (iii) false rejection removal. The method was validated on LGE MR images of 20 chronic postinfarction patients, using manually traced MI contours from two independent observers as reference. Good agreement was observed between automatic and manual MI identification. Validation results showed that the average Dice indices, which describe the percentage of overlap between two regions, were 0.83 +/- 0.07 and 0.79 +/- 0.08 between the automatic identification and the manual tracing from observer 1 and observer 2, and the errors in estimated infarct percentage were 0.0 +/- 1.9% and 3.8 +/- 4.7% compared with observer 1 and observer 2. The difference between the automatic method and manual tracing is in the order of interobserver variation. In conclusion, the developed automatic method is accurate and robust in MI delineation, providing an objective tool for quantitative assessment of MI in LGE MR imaging.

Terminal Sliding Mode Tracking Controller Design for Automatic Guided Vehicle

NASA Astrophysics Data System (ADS)

Chen, Hongbin

2018-03-01

Based on sliding mode variable structure control theory, the path tracking problem of automatic guided vehicle is studied, proposed a controller design method based on the terminal sliding mode. First of all, through analyzing the characteristics of the automatic guided vehicle movement, the kinematics model is presented. Then to improve the traditional expression of terminal sliding mode, design a nonlinear sliding mode which the convergence speed is faster than the former, verified by theoretical analysis, the design of sliding mode is steady and fast convergence in the limited time. Finally combining Lyapunov method to design the tracking control law of automatic guided vehicle, the controller can make the automatic guided vehicle track the desired trajectory in the global sense as well as in finite time. The simulation results verify the correctness and effectiveness of the control law.

Fully automatic assignment of small molecules' NMR spectra without relying on chemical shift predictions.

PubMed

Castillo, Andrés M; Bernal, Andrés; Patiny, Luc; Wist, Julien

2015-08-01

We present a method for the automatic assignment of small molecules' NMR spectra. The method includes an automatic and novel self-consistent peak-picking routine that validates NMR peaks in each spectrum against peaks in the same or other spectra that are due to the same resonances. The auto-assignment routine used is based on branch-and-bound optimization and relies predominantly on integration and correlation data; chemical shift information may be included when available to fasten the search and shorten the list of viable assignments, but in most cases tested, it is not required in order to find the correct assignment. This automatic assignment method is implemented as a web-based tool that runs without any user input other than the acquired spectra. Copyright © 2015 John Wiley & Sons, Ltd.

The myth of harmless wrongs in moral cognition: Automatic dyadic completion from sin to suffering.

PubMed

Gray, Kurt; Schein, Chelsea; Ward, Adrian F

2014-08-01

When something is wrong, someone is harmed. This hypothesis derives from the theory of dyadic morality, which suggests a moral cognitive template of wrongdoing agent and suffering patient (i.e., victim). This dyadic template means that victimless wrongs (e.g., masturbation) are psychologically incomplete, compelling the mind to perceive victims even when they are objectively absent. Five studies reveal that dyadic completion occurs automatically and implicitly: Ostensibly harmless wrongs are perceived to have victims (Study 1), activate concepts of harm (Studies 2 and 3), and increase perceptions of suffering (Studies 4 and 5). These results suggest that perceiving harm in immorality is intuitive and does not require effortful rationalization. This interpretation argues against both standard interpretations of moral dumbfounding and domain-specific theories of morality that assume the psychological existence of harmless wrongs. Dyadic completion also suggests that moral dilemmas in which wrongness (deontology) and harm (utilitarianism) conflict are unrepresentative of typical moral cognition. PsycINFO Database Record (c) 2014 APA, all rights reserved.

A novel automatic quantification method for high-content screening analysis of DNA double strand-break response.

PubMed

Feng, Jingwen; Lin, Jie; Zhang, Pengquan; Yang, Songnan; Sa, Yu; Feng, Yuanming

2017-08-29

High-content screening is commonly used in studies of the DNA damage response. The double-strand break (DSB) is one of the most harmful types of DNA damage lesions. The conventional method used to quantify DSBs is γH2AX foci counting, which requires manual adjustment and preset parameters and is usually regarded as imprecise, time-consuming, poorly reproducible, and inaccurate. Therefore, a robust automatic alternative method is highly desired. In this manuscript, we present a new method for quantifying DSBs which involves automatic image cropping, automatic foci-segmentation and fluorescent intensity measurement. Furthermore, an additional function was added for standardizing the measurement of DSB response inhibition based on co-localization analysis. We tested the method with a well-known inhibitor of DSB response. The new method requires only one preset parameter, which effectively minimizes operator-dependent variations. Compared with conventional methods, the new method detected a higher percentage difference of foci formation between different cells, which can improve measurement accuracy. The effects of the inhibitor on DSB response were successfully quantified with the new method (p = 0.000). The advantages of this method in terms of reliability, automation and simplicity show its potential in quantitative fluorescence imaging studies and high-content screening for compounds and factors involved in DSB response.

The Complete Automation of the Minnesota Multiphasic Personality Inventory and a Study of its Response Latency.

ERIC Educational Resources Information Center

Dunn, Thomas G.; And Others

The feasibility of completely automating the Minnesota Multiphasic Personality Inventory (MMPI) was tested, and item response latencies were compared with other MMPI item characteristics. A total of 26 scales were successfully scored automatically for 165 subjects. The program also typed a Mayo Clinic interpretive report on a computer terminal,…

Resiliency in Physics: The Lived Experiences of African-American Women Who Completed Doctoral Physics Programs

ERIC Educational Resources Information Center

Burnette, Samara Fleming

2013-01-01

Currently, little is known about African-American women with doctoral degrees in physics. This study examined the lived experiences of African-American women who completed doctoral programs in physics. Due to factors of race and gender, African-American women automatically enter a double-bind in science, technology, engineering, and mathematics…

CFD Analysis and Design Optimization Using Parallel Computers

NASA Technical Reports Server (NTRS)

Martinelli, Luigi; Alonso, Juan Jose; Jameson, Antony; Reuther, James

1997-01-01

A versatile and efficient multi-block method is presented for the simulation of both steady and unsteady flow, as well as aerodynamic design optimization of complete aircraft configurations. The compressible Euler and Reynolds Averaged Navier-Stokes (RANS) equations are discretized using a high resolution scheme on body-fitted structured meshes. An efficient multigrid implicit scheme is implemented for time-accurate flow calculations. Optimum aerodynamic shape design is achieved at very low cost using an adjoint formulation. The method is implemented on parallel computing systems using the MPI message passing interface standard to ensure portability. The results demonstrate that, by combining highly efficient algorithms with parallel computing, it is possible to perform detailed steady and unsteady analysis as well as automatic design for complex configurations using the present generation of parallel computers.

Robust extraction of the aorta and pulmonary artery from 3D MDCT image data

NASA Astrophysics Data System (ADS)

Taeprasartsit, Pinyo; Higgins, William E.

2010-03-01

Accurate definition of the aorta and pulmonary artery from three-dimensional (3D) multi-detector CT (MDCT) images is important for pulmonary applications. This work presents robust methods for defining the aorta and pulmonary artery in the central chest. The methods work on both contrast enhanced and no-contrast 3D MDCT image data. The automatic methods use a common approach employing model fitting and selection and adaptive refinement. During the occasional event that more precise vascular extraction is desired or the method fails, we also have an alternate semi-automatic fail-safe method. The semi-automatic method extracts the vasculature by extending the medial axes into a user-guided direction. A ground-truth study over a series of 40 human 3D MDCT images demonstrates the efficacy, accuracy, robustness, and efficiency of the methods.

Automated ambiguity estimation for VLBI Intensive sessions using L1-norm

NASA Astrophysics Data System (ADS)

Kareinen, Niko; Hobiger, Thomas; Haas, Rüdiger

2016-12-01

Very Long Baseline Interferometry (VLBI) is a space-geodetic technique that is uniquely capable of direct observation of the angle of the Earth's rotation about the Celestial Intermediate Pole (CIP) axis, namely UT1. The daily estimates of the difference between UT1 and Coordinated Universal Time (UTC) provided by the 1-h long VLBI Intensive sessions are essential in providing timely UT1 estimates for satellite navigation systems and orbit determination. In order to produce timely UT1 estimates, efforts have been made to completely automate the analysis of VLBI Intensive sessions. This involves the automatic processing of X- and S-band group delays. These data contain an unknown number of integer ambiguities in the observed group delays. They are introduced as a side-effect of the bandwidth synthesis technique, which is used to combine correlator results from the narrow channels that span the individual bands. In an automated analysis with the c5++ software the standard approach in resolving the ambiguities is to perform a simplified parameter estimation using a least-squares adjustment (L2-norm minimisation). We implement L1-norm as an alternative estimation method in c5++. The implemented method is used to automatically estimate the ambiguities in VLBI Intensive sessions on the Kokee-Wettzell baseline. The results are compared to an analysis set-up where the ambiguity estimation is computed using the L2-norm. For both methods three different weighting strategies for the ambiguity estimation are assessed. The results show that the L1-norm is better at automatically resolving the ambiguities than the L2-norm. The use of the L1-norm leads to a significantly higher number of good quality UT1-UTC estimates with each of the three weighting strategies. The increase in the number of sessions is approximately 5% for each weighting strategy. This is accompanied by smaller post-fit residuals in the final UT1-UTC estimation step.

A prototype gas exchange monitor for exercise stress testing aboard NASA Space Station

NASA Technical Reports Server (NTRS)

Orr, Joseph A.; Westenskow, Dwayne R.; Bauer, Anne

1989-01-01

This paper describes an easy-to-use monitor developed to track the weightlessness deconditioning aboard the NASA Space Station, together with the results of testing of a prototype instrument. The monitor measures the O2 uptake and CO2 production, and calculates the maximum O2 uptake and anaerobic threshold during an exercise stress test. The system uses two flowmeters in series to achieve a completely automatic calibration, and uses breath-by-breath compensation for sample line-transport delay. The monitor was evaluated using two laboratory methods and was shown to be accurate. The system's block diagram and the bench test setup diagram are included.

Method and apparatus for eliminating unsuccessful tries in a search tree

NASA Technical Reports Server (NTRS)

Peterson, John C. (Inventor); Chow, Edward (Inventor); Madan, Herb S. (Inventor)

1991-01-01

A circuit switching system in an M-ary, n-cube connected network completes a best-first path from an originating node to a destination node by latching valid legs of the path as the path is being sought out. Each network node is provided with a routing hyperswitch sub-network, (HSN) connected between that node and bidirectional high capacity communication channels of the n-cube network. The sub-networks are all controlled by routing algorithms which respond to message identification headings (headers) on messages to be routed along one or more routing legs. The header includes information embedded therein which is interpreted by each sub-network to route and historically update the header. A logic circuit, available at every node, implements the algorithm and automatically forwards or back-tracks the header in the network legs of various paths until a completed path is latched.

On the dependence of information display quality requirements upon human characteristics and pilot/automatics relations

NASA Technical Reports Server (NTRS)

Wilckens, V.

1972-01-01

Present information display concepts for pilot landing guidance are outlined considering manual control as well as substitution of man by fully competent automatics. Display improvements are achieved by compressing the distributed indicators into an accumulative display and thus reducing information scanning. Complete integration of quantitative indications, outer loop information, and real world display in a pictorial information channel geometry constitutes an interface with human ability to differentiate and integrate for optimal manual control of the aircraft.

Small passenger car transmission test; Ford C4 transmission

NASA Technical Reports Server (NTRS)

Bujold, M. P.

1980-01-01

A 1979 Ford C4 automatic transmission was tested per a passenger car automatic transmission test code (SAE J651b) which required drive performance, coast performance, and no load test conditions. Under these test conditions, the transmission attained maximum efficiencies in the mid-eighty percent range for both drive performance tests and coast performance tests. The major results of this test (torque, speed, and efficiency curves) are presented. Graphs map the complete performance characteristics for the Ford C4 transmission.

Automatic Tool for Local Assembly Structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whole community shotgun sequencing of total DNA (i.e. metagenomics) and total RNA (i.e. metatranscriptomics) has provided a wealth of information in the microbial community structure, predicted functions, metabolic networks, and is even able to reconstruct complete genomes directly. Here we present ATLAS (Automatic Tool for Local Assembly Structures) a comprehensive pipeline for assembly, annotation, genomic binning of metagenomic and metatranscriptomic data with an integrated framework for Multi-Omics. This will provide an open source tool for the Multi-Omic community at large.

Affective decision-making moderates the effects of automatic associations on alcohol use among drug offenders.

PubMed

Cappelli, Christopher; Ames, Susan; Shono, Yusuke; Dust, Mark; Stacy, Alan

2017-09-01

This study used a dual-process model of cognition in order to investigate the possible influence of automatic and deliberative processes on lifetime alcohol use in a sample of drug offenders. The objective was to determine if automatic/implicit associations in memory can exert an influence over an individual's alcohol use and if decision-making ability could potentially modify the influence of these associations. 168 participants completed a battery of cognitive tests measuring implicit alcohol associations in memory (verb generation) as well as their affective decision-making ability (Iowa Gambling Task). Structural equation modeling procedures were used to test the relationship between implicit associations, decision-making, and lifetime alcohol use. Results revealed that among participants with lower levels of decision-making, implicit alcohol associations more strongly predicted higher lifetime alcohol use. These findings provide further support for the interaction between a specific decision function and its influence over automatic processes in regulating alcohol use behavior in a risky population. Understanding the interaction between automatic associations and decision processes may aid in developing more effective intervention components.

[Modeling and implementation method for the automatic biochemistry analyzer control system].

PubMed

Wang, Dong; Ge, Wan-cheng; Song, Chun-lin; Wang, Yun-guang

2009-03-01

In this paper the system structure The automatic biochemistry analyzer is a necessary instrument for clinical diagnostics. First of is analyzed. The system problems description and the fundamental principles for dispatch are brought forward. Then this text puts emphasis on the modeling for the automatic biochemistry analyzer control system. The objects model and the communications model are put forward. Finally, the implementation method is designed. It indicates that the system based on the model has good performance.

Automatics adjusment on private pension fund for Asian Mathematics Conferences

NASA Astrophysics Data System (ADS)

Purwadi, J.

2017-10-01

This paper discussed about how the automatic adjustment mechanism in the pension fund with defined benefits in case conditions beyond assumptions - assumptions that have been determined. Automatic adjustment referred to in this experiment is intended to anticipate changes in economic and demographic conditions. The method discuss in this paper are indexing life expectancy. In this paper discussed about how the methods on private pension fund and how’s the impact of the change of life expectancy on benefit.

Towards the automatic detection and analysis of sunspot rotation

NASA Astrophysics Data System (ADS)

Brown, Daniel S.; Walker, Andrew P.

2016-10-01

Torsional rotation of sunspots have been noted by many authors over the past century. Sunspots have been observed to rotate up to the order of 200 degrees over 8-10 days, and these have often been linked with eruptive behaviour such as solar flares and coronal mass ejections. However, most studies in the literature are case studies or small-number studies which suffer from selection bias. In order to better understand sunspot rotation and its impact on the corona, unbiased large-sample statistical studies are required (including both rotating and non-rotating sunspots). While this can be done manually, a better approach is to automate the detection and analysis of rotating sunspots using robust methods with well characterised uncertainties. The SDO/HMI instrument provide long-duration, high-resolution and high-cadence continuum observations suitable for extracting a large number of examples of rotating sunspots. This presentation will outline the analysis of SDI/HMI data to determine the rotation (and non-rotation) profiles of sunspots for the complete duration of their transit across the solar disk, along with how this can be extended to automatically identify sunspots and initiate their analysis.

Automatic Assignment of Methyl-NMR Spectra of Supramolecular Machines Using Graph Theory.

PubMed

Pritišanac, Iva; Degiacomi, Matteo T; Alderson, T Reid; Carneiro, Marta G; Ab, Eiso; Siegal, Gregg; Baldwin, Andrew J

2017-07-19

Methyl groups are powerful probes for the analysis of structure, dynamics and function of supramolecular assemblies, using both solution- and solid-state NMR. Widespread application of the methodology has been limited due to the challenges associated with assigning spectral resonances to specific locations within a biomolecule. Here, we present Methyl Assignment by Graph Matching (MAGMA), for the automatic assignment of methyl resonances. A graph matching protocol examines all possibilities for each resonance in order to determine an exact assignment that includes a complete description of any ambiguity. MAGMA gives 100% accuracy in confident assignments when tested against both synthetic data, and 9 cross-validated examples using both solution- and solid-state NMR data. We show that this remarkable accuracy enables a user to distinguish between alternative protein structures. In a drug discovery application on HSP90, we show the method can rapidly and efficiently distinguish between possible ligand binding modes. By providing an exact and robust solution to methyl resonance assignment, MAGMA can facilitate significantly accelerated studies of supramolecular machines using methyl-based NMR spectroscopy.

Semi-automatic 2D-to-3D conversion of human-centered videos enhanced by age and gender estimation

NASA Astrophysics Data System (ADS)

Fard, Mani B.; Bayazit, Ulug

2014-01-01

In this work, we propose a feasible 3D video generation method to enable high quality visual perception using a monocular uncalibrated camera. Anthropometric distances between face standard landmarks are approximated based on the person's age and gender. These measurements are used in a 2-stage approach to facilitate the construction of binocular stereo images. Specifically, one view of the background is registered in initial stage of video shooting. It is followed by an automatically guided displacement of the camera toward its secondary position. At the secondary position the real-time capturing is started and the foreground (viewed person) region is extracted for each frame. After an accurate parallax estimation the extracted foreground is placed in front of the background image that was captured at the initial position. So the constructed full view of the initial position combined with the view of the secondary (current) position, form the complete binocular pairs during real-time video shooting. The subjective evaluation results present a competent depth perception quality through the proposed system.

A comparative study on different methods of automatic mesh generation of human femurs.

PubMed

Viceconti, M; Bellingeri, L; Cristofolini, L; Toni, A

1998-01-01

The aim of this study was to evaluate comparatively five methods for automating mesh generation (AMG) when used to mesh a human femur. The five AMG methods considered were: mapped mesh, which provides hexahedral elements through a direct mapping of the element onto the geometry; tetra mesh, which generates tetrahedral elements from a solid model of the object geometry; voxel mesh which builds cubic 8-node elements directly from CT images; and hexa mesh that automatically generated hexahedral elements from a surface definition of the femur geometry. The various methods were tested against two reference models: a simplified geometric model and a proximal femur model. The first model was useful to assess the inherent accuracy of the meshes created by the AMG methods, since an analytical solution was available for the elastic problem of the simplified geometric model. The femur model was used to test the AMG methods in a more realistic condition. The femoral geometry was derived from a reference model (the "standardized femur") and the finite element analyses predictions were compared to experimental measurements. All methods were evaluated in terms of human and computer effort needed to carry out the complete analysis, and in terms of accuracy. The comparison demonstrated that each tested method deserves attention and may be the best for specific situations. The mapped AMG method requires a significant human effort but is very accurate and it allows a tight control of the mesh structure. The tetra AMG method requires a solid model of the object to be analysed but is widely available and accurate. The hexa AMG method requires a significant computer effort but can also be used on polygonal models and is very accurate. The voxel AMG method requires a huge number of elements to reach an accuracy comparable to that of the other methods, but it does not require any pre-processing of the CT dataset to extract the geometry and in some cases may be the only viable solution.

A Domain-Decomposed Multilevel Method for Adaptively Refined Cartesian Grids with Embedded Boundaries

NASA Technical Reports Server (NTRS)

Aftosmis, M. J.; Berger, M. J.; Adomavicius, G.

2000-01-01

Preliminary verification and validation of an efficient Euler solver for adaptively refined Cartesian meshes with embedded boundaries is presented. The parallel, multilevel method makes use of a new on-the-fly parallel domain decomposition strategy based upon the use of space-filling curves, and automatically generates a sequence of coarse meshes for processing by the multigrid smoother. The coarse mesh generation algorithm produces grids which completely cover the computational domain at every level in the mesh hierarchy. A series of examples on realistically complex three-dimensional configurations demonstrate that this new coarsening algorithm reliably achieves mesh coarsening ratios in excess of 7 on adaptively refined meshes. Numerical investigations of the scheme's local truncation error demonstrate an achieved order of accuracy between 1.82 and 1.88. Convergence results for the multigrid scheme are presented for both subsonic and transonic test cases and demonstrate W-cycle multigrid convergence rates between 0.84 and 0.94. Preliminary parallel scalability tests on both simple wing and complex complete aircraft geometries shows a computational speedup of 52 on 64 processors using the run-time mesh partitioner.

Process weakness assessment by profiling all incoming design components

NASA Astrophysics Data System (ADS)

Zhuang, Linda; Cai, MengFeng; Zhu, Annie; Zhang, Yifan; Sweis, Jason; Lai, Ya-Chieh

2017-03-01

Foundries normally receive a large number of designs from different customers every day. It is desired to automatically profile each incoming design to quantify certain metrics like 1) the number of polygons per GDS layers 2) what kind of electrical components the design contains 3) what the dimensions of each electrical component are 4) how frequently any size of components have been used and their physical locations. This paper will present a novel method of how to generate a complete profile of components for any particular design. The component checking flow need to be completed within hours so it will have very little impact on the tape-out time. A pre-layer checking method is also run to group commonly used layers for different electrical components and then employ different layout profiling flows. The foundry does this design chip analysis in order to find potentially weak devices due to their size or special size requirements for particular electrical components. The foundry can then take pre-emptive action to avoid yield loss or make an unnecessary mask for new incoming products before fab processing starts.

Semi-automatic mapping of cultural heritage from airborne laser scanning using deep learning

NASA Astrophysics Data System (ADS)

Due Trier, Øivind; Salberg, Arnt-Børre; Holger Pilø, Lars; Tonning, Christer; Marius Johansen, Hans; Aarsten, Dagrun

2016-04-01

This paper proposes to use deep learning to improve semi-automatic mapping of cultural heritage from airborne laser scanning (ALS) data. Automatic detection methods, based on traditional pattern recognition, have been applied in a number of cultural heritage mapping projects in Norway for the past five years. Automatic detection of pits and heaps have been combined with visual interpretation of the ALS data for the mapping of deer hunting systems, iron production sites, grave mounds and charcoal kilns. However, the performance of the automatic detection methods varies substantially between ALS datasets. For the mapping of deer hunting systems on flat gravel and sand sediment deposits, the automatic detection results were almost perfect. However, some false detections appeared in the terrain outside of the sediment deposits. These could be explained by other pit-like landscape features, like parts of river courses, spaces between boulders, and modern terrain modifications. However, these were easy to spot during visual interpretation, and the number of missed individual pitfall traps was still low. For the mapping of grave mounds, the automatic method produced a large number of false detections, reducing the usefulness of the semi-automatic approach. The mound structure is a very common natural terrain feature, and the grave mounds are less distinct in shape than the pitfall traps. Still, applying automatic mound detection on an entire municipality did lead to a new discovery of an Iron Age grave field with more than 15 individual mounds. Automatic mound detection also proved to be useful for a detailed re-mapping of Norway's largest Iron Age grave yard, which contains almost 1000 individual graves. Combined pit and mound detection has been applied to the mapping of more than 1000 charcoal kilns that were used by an iron work 350-200 years ago. The majority of charcoal kilns were indirectly detected as either pits on the circumference, a central mound, or both. However, kilns with a flat interior and a shallow ditch along the circumference were often missed by the automatic detection method. The successfulness of automatic detection seems to depend on two factors: (1) the density of ALS ground hits on the cultural heritage structures being sought, and (2) to what extent these structures stand out from natural terrain structures. The first factor may, to some extent, be improved by using a higher number of ALS pulses per square meter. The second factor is difficult to change, and also highlights another challenge: how to make a general automatic method that is applicable in all types of terrain within a country. The mixed experience with traditional pattern recognition for semi-automatic mapping of cultural heritage led us to consider deep learning as an alternative approach. The main principle is that a general feature detector has been trained on a large image database. The feature detector is then tailored to a specific task by using a modest number of images of true and false examples of the features being sought. Results of using deep learning are compared with previous results using traditional pattern recognition.

Automatic localization of bifurcations and vessel crossings in digital fundus photographs using location regression

NASA Astrophysics Data System (ADS)

Niemeijer, Meindert; Dumitrescu, Alina V.; van Ginneken, Bram; Abrámoff, Michael D.

2011-03-01

Parameters extracted from the vasculature on the retina are correlated with various conditions such as diabetic retinopathy and cardiovascular diseases such as stroke. Segmentation of the vasculature on the retina has been a topic that has received much attention in the literature over the past decade. Analysis of the segmentation result, however, has only received limited attention with most works describing methods to accurately measure the width of the vessels. Analyzing the connectedness of the vascular network is an important step towards the characterization of the complete vascular tree. The retinal vascular tree, from an image interpretation point of view, originates at the optic disc and spreads out over the retina. The tree bifurcates and the vessels also cross each other. The points where this happens form the key to determining the connectedness of the complete tree. We present a supervised method to detect the bifurcations and crossing points of the vasculature of the retina. The method uses features extracted from the vasculature as well as the image in a location regression approach to find those locations of the segmented vascular tree where the bifurcation or crossing occurs (from here, POI, points of interest). We evaluate the method on the publicly available DRIVE database in which an ophthalmologist has marked the POI.

Automatic Annotation Method on Learners' Opinions in Case Method Discussion

ERIC Educational Resources Information Center

Samejima, Masaki; Hisakane, Daichi; Komoda, Norihisa

2015-01-01

Purpose: The purpose of this paper is to annotate an attribute of a problem, a solution or no annotation on learners' opinions automatically for supporting the learners' discussion without a facilitator. The case method aims at discussing problems and solutions in a target case. However, the learners miss discussing some of problems and solutions.…

A new method for the automatic interpretation of Schlumberger and Wenner sounding curves

USGS Publications Warehouse

Zohdy, A.A.R.

1989-01-01

A fast iterative method for the automatic interpretation of Schlumberger and Wenner sounding curves is based on obtaining interpreted depths and resistivities from shifted electrode spacings and adjusted apparent resistivities, respectively. The method is fully automatic. It does not require an initial guess of the number of layers, their thicknesses, or their resistivities; and it does not require extrapolation of incomplete sounding curves. The number of layers in the interpreted model equals the number of digitized points on the sounding curve. The resulting multilayer model is always well-behaved with no thin layers of unusually high or unusually low resistivities. For noisy data, interpretation is done in two sets of iterations (two passes). Anomalous layers, created because of noise in the first pass, are eliminated in the second pass. Such layers are eliminated by considering the best-fitting curve from the first pass to be a smoothed version of the observed curve and automatically reinterpreting it (second pass). The application of the method is illustrated by several examples. -Author

A Modular Hierarchical Approach to 3D Electron Microscopy Image Segmentation

PubMed Central

Liu, Ting; Jones, Cory; Seyedhosseini, Mojtaba; Tasdizen, Tolga

2014-01-01

The study of neural circuit reconstruction, i.e., connectomics, is a challenging problem in neuroscience. Automated and semi-automated electron microscopy (EM) image analysis can be tremendously helpful for connectomics research. In this paper, we propose a fully automatic approach for intra-section segmentation and inter-section reconstruction of neurons using EM images. A hierarchical merge tree structure is built to represent multiple region hypotheses and supervised classification techniques are used to evaluate their potentials, based on which we resolve the merge tree with consistency constraints to acquire final intra-section segmentation. Then, we use a supervised learning based linking procedure for the inter-section neuron reconstruction. Also, we develop a semi-automatic method that utilizes the intermediate outputs of our automatic algorithm and achieves intra-segmentation with minimal user intervention. The experimental results show that our automatic method can achieve close-to-human intra-segmentation accuracy and state-of-the-art inter-section reconstruction accuracy. We also show that our semi-automatic method can further improve the intra-segmentation accuracy. PMID:24491638

Automatic Syllabification in English: A Comparison of Different Algorithms

ERIC Educational Resources Information Center

Marchand, Yannick; Adsett, Connie R.; Damper, Robert I.

2009-01-01

Automatic syllabification of words is challenging, not least because the syllable is not easy to define precisely. Consequently, no accepted standard algorithm for automatic syllabification exists. There are two broad approaches: rule-based and data-driven. The rule-based method effectively embodies some theoretical position regarding the…

Masked Priming Effects in Aphasia: Evidence of Altered Automatic Spreading Activation

ERIC Educational Resources Information Center

Silkes, JoAnn P.; Rogers, Margaret A.

2012-01-01

Purpose: Previous research has suggested that impairments of automatic spreading activation may underlie some aphasic language deficits. The current study further investigated the status of automatic spreading activation in individuals with aphasia as compared with typical adults. Method: Participants were 21 individuals with aphasia (12 fluent, 9…

A Robust Gradient Based Method for Building Extraction from LiDAR and Photogrammetric Imagery.

PubMed

Siddiqui, Fasahat Ullah; Teng, Shyh Wei; Awrangjeb, Mohammad; Lu, Guojun

2016-07-19

Existing automatic building extraction methods are not effective in extracting buildings which are small in size and have transparent roofs. The application of large area threshold prohibits detection of small buildings and the use of ground points in generating the building mask prevents detection of transparent buildings. In addition, the existing methods use numerous parameters to extract buildings in complex environments, e.g., hilly area and high vegetation. However, the empirical tuning of large number of parameters reduces the robustness of building extraction methods. This paper proposes a novel Gradient-based Building Extraction (GBE) method to address these limitations. The proposed method transforms the Light Detection And Ranging (LiDAR) height information into intensity image without interpolation of point heights and then analyses the gradient information in the image. Generally, building roof planes have a constant height change along the slope of a roof plane whereas trees have a random height change. With such an analysis, buildings of a greater range of sizes with a transparent or opaque roof can be extracted. In addition, a local colour matching approach is introduced as a post-processing stage to eliminate trees. This stage of our proposed method does not require any manual setting and all parameters are set automatically from the data. The other post processing stages including variance, point density and shadow elimination are also applied to verify the extracted buildings, where comparatively fewer empirically set parameters are used. The performance of the proposed GBE method is evaluated on two benchmark data sets by using the object and pixel based metrics (completeness, correctness and quality). Our experimental results show the effectiveness of the proposed method in eliminating trees, extracting buildings of all sizes, and extracting buildings with and without transparent roof. When compared with current state-of-the-art building extraction methods, the proposed method outperforms the existing methods in various evaluation metrics.

A Robust Gradient Based Method for Building Extraction from LiDAR and Photogrammetric Imagery

PubMed Central

Siddiqui, Fasahat Ullah; Teng, Shyh Wei; Awrangjeb, Mohammad; Lu, Guojun

2016-01-01

Existing automatic building extraction methods are not effective in extracting buildings which are small in size and have transparent roofs. The application of large area threshold prohibits detection of small buildings and the use of ground points in generating the building mask prevents detection of transparent buildings. In addition, the existing methods use numerous parameters to extract buildings in complex environments, e.g., hilly area and high vegetation. However, the empirical tuning of large number of parameters reduces the robustness of building extraction methods. This paper proposes a novel Gradient-based Building Extraction (GBE) method to address these limitations. The proposed method transforms the Light Detection And Ranging (LiDAR) height information into intensity image without interpolation of point heights and then analyses the gradient information in the image. Generally, building roof planes have a constant height change along the slope of a roof plane whereas trees have a random height change. With such an analysis, buildings of a greater range of sizes with a transparent or opaque roof can be extracted. In addition, a local colour matching approach is introduced as a post-processing stage to eliminate trees. This stage of our proposed method does not require any manual setting and all parameters are set automatically from the data. The other post processing stages including variance, point density and shadow elimination are also applied to verify the extracted buildings, where comparatively fewer empirically set parameters are used. The performance of the proposed GBE method is evaluated on two benchmark data sets by using the object and pixel based metrics (completeness, correctness and quality). Our experimental results show the effectiveness of the proposed method in eliminating trees, extracting buildings of all sizes, and extracting buildings with and without transparent roof. When compared with current state-of-the-art building extraction methods, the proposed method outperforms the existing methods in various evaluation metrics. PMID:27447631

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pichara, Karim; Protopapas, Pavlos

We present an automatic classification method for astronomical catalogs with missing data. We use Bayesian networks and a probabilistic graphical model that allows us to perform inference to predict missing values given observed data and dependency relationships between variables. To learn a Bayesian network from incomplete data, we use an iterative algorithm that utilizes sampling methods and expectation maximization to estimate the distributions and probabilistic dependencies of variables from data with missing values. To test our model, we use three catalogs with missing data (SAGE, Two Micron All Sky Survey, and UBVI) and one complete catalog (MACHO). We examine howmore » classification accuracy changes when information from missing data catalogs is included, how our method compares to traditional missing data approaches, and at what computational cost. Integrating these catalogs with missing data, we find that classification of variable objects improves by a few percent and by 15% for quasar detection while keeping the computational cost the same.« less

The use of the wavelet cluster analysis for asteroid family determination

NASA Technical Reports Server (NTRS)

Benjoya, Phillippe; Slezak, E.; Froeschle, Claude

1992-01-01

The asteroid family determination has been analysis method dependent for a longtime. A new cluster analysis based on the wavelet transform has allowed an automatic definition of families with a degree of significance versus randomness. Actually this method is rather general and can be applied to any kind of structural analysis. We will rather concentrate on the main features of the method. The analysis has been performed on the set of 4100 asteroid proper elements computed by Milani and Knezevic (see Milani and Knezevic 1990). Twenty one families have been found and influence of the chosen metric has been tested. The results have beem compared to Zappala et al.'s ones (see Zappala et al 1990) obtained by the use of a completely different method applied to the same set of data. For the first time, a good overlapping has been found between both method results, not only for the big well known families but also for the smallest ones.

Expert Knowledge-Based Automatic Sleep Stage Determination by Multi-Valued Decision Making Method

NASA Astrophysics Data System (ADS)

Wang, Bei; Sugi, Takenao; Kawana, Fusae; Wang, Xingyu; Nakamura, Masatoshi

In this study, an expert knowledge-based automatic sleep stage determination system working on a multi-valued decision making method is developed. Visual inspection by a qualified clinician is adopted to obtain the expert knowledge database. The expert knowledge database consists of probability density functions of parameters for various sleep stages. Sleep stages are determined automatically according to the conditional probability. Totally, four subjects were participated. The automatic sleep stage determination results showed close agreements with the visual inspection on sleep stages of awake, REM (rapid eye movement), light sleep and deep sleep. The constructed expert knowledge database reflects the distributions of characteristic parameters which can be adaptive to variable sleep data in hospitals. The developed automatic determination technique based on expert knowledge of visual inspection can be an assistant tool enabling further inspection of sleep disorder cases for clinical practice.

Phantom Study Investigating the Accuracy of Manual and Automatic Image Fusion with the GE Logiq E9: Implications for use in Percutaneous Liver Interventions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burgmans, Mark Christiaan, E-mail: m.c.burgmans@lumc.nl; Harder, J. Michiel den, E-mail: chiel.den.harder@gmail.com; Meershoek, Philippa, E-mail: P.Meershoek@lumc.nl

PurposeTo determine the accuracy of automatic and manual co-registration methods for image fusion of three-dimensional computed tomography (CT) with real-time ultrasonography (US) for image-guided liver interventions.Materials and MethodsCT images of a skills phantom with liver lesions were acquired and co-registered to US using GE Logiq E9 navigation software. Manual co-registration was compared to automatic and semiautomatic co-registration using an active tracker. Also, manual point registration was compared to plane registration with and without an additional translation point. Finally, comparison was made between manual and automatic selection of reference points. In each experiment, accuracy of the co-registration method was determined bymore » measurement of the residual displacement in phantom lesions by two independent observers.ResultsMean displacements for a superficial and deep liver lesion were comparable after manual and semiautomatic co-registration: 2.4 and 2.0 mm versus 2.0 and 2.5 mm, respectively. Both methods were significantly better than automatic co-registration: 5.9 and 5.2 mm residual displacement (p < 0.001; p < 0.01). The accuracy of manual point registration was higher than that of plane registration, the latter being heavily dependent on accurate matching of axial CT and US images by the operator. Automatic reference point selection resulted in significantly lower registration accuracy compared to manual point selection despite lower root-mean-square deviation (RMSD) values.ConclusionThe accuracy of manual and semiautomatic co-registration is better than that of automatic co-registration. For manual co-registration using a plane, choosing the correct plane orientation is an essential first step in the registration process. Automatic reference point selection based on RMSD values is error-prone.« less

Experimental research on showing automatic disappearance pen handwriting based on spectral imaging technology

NASA Astrophysics Data System (ADS)

Su, Yi; Xu, Lei; Liu, Ningning; Huang, Wei; Xu, Xiaojing

2016-10-01

Purpose to find an efficient, non-destructive examining method for showing the disappearing words after writing with automatic disappearance pen. Method Using the imaging spectrometer to show the potential disappearance words on paper surface according to different properties of reflection absorbed by various substances in different bands. Results the disappeared words by using different disappearance pens to write on the same paper or the same disappearance pen to write on different papers, both can get good show results through the use of the spectral imaging examining methods. Conclusion Spectral imaging technology can show the disappearing words after writing by using the automatic disappearance pen.

A new method for automatic discontinuity traces sampling on rock mass 3D model

NASA Astrophysics Data System (ADS)

Umili, G.; Ferrero, A.; Einstein, H. H.

2013-02-01

A new automatic method for discontinuity traces mapping and sampling on a rock mass digital model is described in this work. The implemented procedure allows one to automatically identify discontinuity traces on a Digital Surface Model: traces are detected directly as surface breaklines, by means of maximum and minimum principal curvature values of the vertices that constitute the model surface. Color influence and user errors, that usually characterize the trace mapping on images, are eliminated. Also trace sampling procedures based on circular windows and circular scanlines have been implemented: they are used to infer trace data and to calculate values of mean trace length, expected discontinuity diameter and intensity of rock discontinuities. The method is tested on a case study: results obtained applying the automatic procedure on the DSM of a rock face are compared to those obtained performing a manual sampling on the orthophotograph of the same rock face.

Automatic extraction of discontinuity orientation from rock mass surface 3D point cloud

NASA Astrophysics Data System (ADS)

Chen, Jianqin; Zhu, Hehua; Li, Xiaojun

2016-10-01

This paper presents a new method for extracting discontinuity orientation automatically from rock mass surface 3D point cloud. The proposed method consists of four steps: (1) automatic grouping of discontinuity sets using an improved K-means clustering method, (2) discontinuity segmentation and optimization, (3) discontinuity plane fitting using Random Sample Consensus (RANSAC) method, and (4) coordinate transformation of discontinuity plane. The method is first validated by the point cloud of a small piece of a rock slope acquired by photogrammetry. The extracted discontinuity orientations are compared with measured ones in the field. Then it is applied to a publicly available LiDAR data of a road cut rock slope at Rockbench repository. The extracted discontinuity orientations are compared with the method proposed by Riquelme et al. (2014). The results show that the presented method is reliable and of high accuracy, and can meet the engineering needs.

Automatic extraction of tree crowns from aerial imagery in urban environment

NASA Astrophysics Data System (ADS)

Liu, Jiahang; Li, Deren; Qin, Xunwen; Yang, Jianfeng

2006-10-01

Traditionally, field-based investigation is the main method to investigate greenbelt in urban environment, which is costly and low updating frequency. In higher resolution image, the imagery structure and texture of tree canopy has great similarity in statistics despite the great difference in configurations of tree canopy, and their surface structures and textures of tree crown are very different from the other types. In this paper, we present an automatic method to detect tree crowns using high resolution image in urban environment without any apriori knowledge. Our method catches unique structure and texture of tree crown surface, use variance and mathematical expectation of defined image window to position the candidate canopy blocks coarsely, then analysis their inner structure and texture to refine these candidate blocks. The possible spans of all the feature parameters used in our method automatically generate from the small number of samples, and HOLE and its distribution as an important characteristics are introduced into refining processing. Also the isotropy of candidate image block and holes' distribution is integrated in our method. After introduction the theory of our method, aerial imageries were used ( with a resolution about 0.3m ) to test our method, and the results indicate that our method is an effective approach to automatically detect tree crown in urban environment.

Automatic lumbar spine measurement in CT images

NASA Astrophysics Data System (ADS)

Mao, Yunxiang; Zheng, Dong; Liao, Shu; Peng, Zhigang; Yan, Ruyi; Liu, Junhua; Dong, Zhongxing; Gong, Liyan; Zhou, Xiang Sean; Zhan, Yiqiang; Fei, Jun

2017-03-01

Accurate lumbar spine measurement in CT images provides an essential way for quantitative spinal diseases analysis such as spondylolisthesis and scoliosis. In today's clinical workflow, the measurements are manually performed by radiologists and surgeons, which is time consuming and irreproducible. Therefore, automatic and accurate lumbar spine measurement algorithm becomes highly desirable. In this study, we propose a method to automatically calculate five different lumbar spine measurements in CT images. There are three main stages of the proposed method: First, a learning based spine labeling method, which integrates both the image appearance and spine geometry information, is used to detect lumbar and sacrum vertebrae in CT images. Then, a multiatlases based image segmentation method is used to segment each lumbar vertebra and the sacrum based on the detection result. Finally, measurements are derived from the segmentation result of each vertebra. Our method has been evaluated on 138 spinal CT scans to automatically calculate five widely used clinical spine measurements. Experimental results show that our method can achieve more than 90% success rates across all the measurements. Our method also significantly improves the measurement efficiency compared to manual measurements. Besides benefiting the routine clinical diagnosis of spinal diseases, our method also enables the large scale data analytics for scientific and clinical researches.

Image analysis for skeletal evaluation of carpal bones

NASA Astrophysics Data System (ADS)

Ko, Chien-Chuan; Mao, Chi-Wu; Lin, Chi-Jen; Sun, Yung-Nien

1995-04-01

The assessment of bone age is an important field to the pediatric radiology. It provides very important information for treatment and prediction of skeletal growth in a developing child. So far, various computerized algorithms for automatically assessing the skeletal growth have been reported. Most of these methods made attempt to analyze the phalangeal growth. The most fundamental step in these automatic measurement methods is the image segmentation that extracts bones from soft-tissue and background. These automatic segmentation methods of hand radiographs can roughly be categorized into two main approaches that are edge and region based methods. This paper presents a region-based carpal-bone segmentation approach. It is organized into four stages: contrast enhancement, moment-preserving thresholding, morphological processing, and region-growing labeling.

2D automatic body-fitted structured mesh generation using advancing extraction method

NASA Astrophysics Data System (ADS)

Zhang, Yaoxin; Jia, Yafei

2018-01-01

This paper presents an automatic mesh generation algorithm for body-fitted structured meshes in Computational Fluids Dynamics (CFD) analysis using the Advancing Extraction Method (AEM). The method is applicable to two-dimensional domains with complex geometries, which have the hierarchical tree-like topography with extrusion-like structures (i.e., branches or tributaries) and intrusion-like structures (i.e., peninsula or dikes). With the AEM, the hierarchical levels of sub-domains can be identified, and the block boundary of each sub-domain in convex polygon shape in each level can be extracted in an advancing scheme. In this paper, several examples were used to illustrate the effectiveness and applicability of the proposed algorithm for automatic structured mesh generation, and the implementation of the method.

Reducing workpieces to their base geometry for multi-step incremental forming using manifold harmonics

NASA Astrophysics Data System (ADS)

Carette, Yannick; Vanhove, Hans; Duflou, Joost

2018-05-01

Single Point Incremental Forming is a flexible process that is well-suited for small batch production and rapid prototyping of complex sheet metal parts. The distributed nature of the deformation process and the unsupported sheet imply that controlling the final accuracy of the workpiece is challenging. To improve the process limits and the accuracy of SPIF, the use of multiple forming passes has been proposed and discussed by a number of authors. Most methods use multiple intermediate models, where the previous one is strictly smaller than the next one, while gradually increasing the workpieces' wall angles. Another method that can be used is the manufacture of a smoothed-out "base geometry" in the first pass, after which more detailed features can be added in subsequent passes. In both methods, the selection of these intermediate shapes is freely decided by the user. However, their practical implementation in the production of complex freeform parts is not straightforward. The original CAD model can be manually adjusted or completely new CAD models can be created. This paper discusses an automatic method that is able to extract the base geometry from a full STL-based CAD model in an analytical way. Harmonic decomposition is used to express the final geometry as the sum of individual surface harmonics. It is then possible to filter these harmonic contributions to obtain a new CAD model with a desired level of geometric detail. This paper explains the technique and its implementation, as well as its use in the automatic generation of multi-step geometries.

Design of automatic startup and shutdown logic for a Brayton-cycle 2- to 15-kilowatt engine

NASA Technical Reports Server (NTRS)

Vrancik, J. E.; Bainbridge, R. C.

1975-01-01

The NASA Lewis Research Center is conducting a closed-Brayton-cycle power conversion system technology program in which a complete power system (engine) has been designed and demonstrated. This report discusses the design of automatic startup and shutdown logic circuits as a modification to the control system presently used in this demonstration engine. This modification was primarily intended to make starting the engine as simple and safe as possible and to allow the engine to be run unattended. In the modified configuration the engine is started by turning the control console power on and pushing the start button after preheating the gas loop. No other operator action is required to effect a complete startup. Shutdown, if one is required, is also effected by a simple stop button. The automatic startup and shutdown of the engine have been successfully and purposefully demonstrated more than 50 times at the Lewis Research Center during 10,000 hours of unattended operation. The net effect of this modification is an engine that can be safely started and stopped by relatively untrained personnel. The approach lends itself directly to remote unattended operation.

SU-E-J-16: Automatic Image Contrast Enhancement Based On Automatic Parameter Optimization for Radiation Therapy Setup Verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qiu, J; Washington University in St Louis, St Louis, MO; Li, H. Harlod

Purpose: In RT patient setup 2D images, tissues often cannot be seen well due to the lack of image contrast. Contrast enhancement features provided by image reviewing software, e.g. Mosaiq and ARIA, require manual selection of the image processing filters and parameters thus inefficient and cannot be automated. In this work, we developed a novel method to automatically enhance the 2D RT image contrast to allow automatic verification of patient daily setups as a prerequisite step of automatic patient safety assurance. Methods: The new method is based on contrast limited adaptive histogram equalization (CLAHE) and high-pass filtering algorithms. The mostmore » important innovation is to automatically select the optimal parameters by optimizing the image contrast. The image processing procedure includes the following steps: 1) background and noise removal, 2) hi-pass filtering by subtracting the Gaussian smoothed Result, and 3) histogram equalization using CLAHE algorithm. Three parameters were determined through an iterative optimization which was based on the interior-point constrained optimization algorithm: the Gaussian smoothing weighting factor, the CLAHE algorithm block size and clip limiting parameters. The goal of the optimization is to maximize the entropy of the processed Result. Results: A total 42 RT images were processed. The results were visually evaluated by RT physicians and physicists. About 48% of the images processed by the new method were ranked as excellent. In comparison, only 29% and 18% of the images processed by the basic CLAHE algorithm and by the basic window level adjustment process, were ranked as excellent. Conclusion: This new image contrast enhancement method is robust and automatic, and is able to significantly outperform the basic CLAHE algorithm and the manual window-level adjustment process that are currently used in clinical 2D image review software tools.« less

Examination of the semi-automatic calculation technique of vegetation cover rate by digital camera images.

NASA Astrophysics Data System (ADS)

Takemine, S.; Rikimaru, A.; Takahashi, K.

The rice is one of the staple foods in the world High quality rice production requires periodically collecting rice growth data to control the growth of rice The height of plant the number of stem the color of leaf is well known parameters to indicate rice growth Rice growth diagnosis method based on these parameters is used operationally in Japan although collecting these parameters by field survey needs a lot of labor and time Recently a laborsaving method for rice growth diagnosis is proposed which is based on vegetation cover rate of rice Vegetation cover rate of rice is calculated based on discriminating rice plant areas in a digital camera image which is photographed in nadir direction Discrimination of rice plant areas in the image was done by the automatic binarization processing However in the case of vegetation cover rate calculation method depending on the automatic binarization process there is a possibility to decrease vegetation cover rate against growth of rice In this paper a calculation method of vegetation cover rate was proposed which based on the automatic binarization process and referred to the growth hysteresis information For several images obtained by field survey during rice growing season vegetation cover rate was calculated by the conventional automatic binarization processing and the proposed method respectively And vegetation cover rate of both methods was compared with reference value obtained by visual interpretation As a result of comparison the accuracy of discriminating rice plant areas was increased by the proposed

Quantitative analysis of the patellofemoral motion pattern using semi-automatic processing of 4D CT data.

PubMed

Forsberg, Daniel; Lindblom, Maria; Quick, Petter; Gauffin, Håkan

2016-09-01

To present a semi-automatic method with minimal user interaction for quantitative analysis of the patellofemoral motion pattern. 4D CT data capturing the patellofemoral motion pattern of a continuous flexion and extension were collected for five patients prone to patellar luxation both pre- and post-surgically. For the proposed method, an observer would place landmarks in a single 3D volume, which then are automatically propagated to the other volumes in a time sequence. From the landmarks in each volume, the measures patellar displacement, patellar tilt and angle between femur and tibia were computed. Evaluation of the observer variability showed the proposed semi-automatic method to be favorable over a fully manual counterpart, with an observer variability of approximately 1.5[Formula: see text] for the angle between femur and tibia, 1.5 mm for the patellar displacement, and 4.0[Formula: see text]-5.0[Formula: see text] for the patellar tilt. The proposed method showed that surgery reduced the patellar displacement and tilt at maximum extension with approximately 10-15 mm and 15[Formula: see text]-20[Formula: see text] for three patients but with less evident differences for two of the patients. A semi-automatic method suitable for quantification of the patellofemoral motion pattern as captured by 4D CT data has been presented. Its observer variability is on par with that of other methods but with the distinct advantage to support continuous motions during the image acquisition.

Observing control and data reduction at the UKIRT

NASA Astrophysics Data System (ADS)

Bridger, Alan; Economou, Frossie; Wright, Gillian S.; Currie, Malcolm J.

1998-07-01

For the past seven years observing with the major instruments at the United Kingdom IR Telescope (UKIRT) has been semi-automated, using ASCII files top configure the instruments and then sequence a series of exposures and telescope movements to acquire the data. For one instrument automatic data reduction completes the cycle. The emergence of recent software technologies has suggested an evolution of this successful system to provide a friendlier and more powerful interface to observing at UKIRT. The Observatory Reduction and Acquisition Control (ORAC) project is now underway to construct this system. A key aim of ORAC is to allow a more complete description of the observing program, including the target sources and the recipe that will be used to provide on-line data reduction. Remote observation preparation and submission will also be supported. In parallel the observatory control system will be upgraded to use these descriptions for more automatic observing, while retaining the 'classical' interactive observing mode. The final component of the project is an improved automatic data reduction system, allowing on-line reduction of data at the telescope while retaining the flexibility to cope with changing observing techniques and instruments. The user will also automatically be provided with the scripts used for the real-time reduction to help provide post-observing data reduction support. The overall project goal is to improve the scientific productivity of the telescope, but it should also reduce the overall ongoing support requirements, and has the eventual goal of supporting the use of queue- scheduled observing.

Automatic tracking of red blood cells in micro channels using OpenCV

NASA Astrophysics Data System (ADS)

Rodrigues, Vânia; Rodrigues, Pedro J.; Pereira, Ana I.; Lima, Rui

2013-10-01

The present study aims to developan automatic method able to track red blood cells (RBCs) trajectories flowing through a microchannel using the Open Source Computer Vision (OpenCV). The developed method is based on optical flux calculation assisted by the maximization of the template-matching product. The experimental results show a good functional performance of this method.

Automatic segmentation of coronary arteries from computed tomography angiography data cloud using optimal thresholding

NASA Astrophysics Data System (ADS)

Ansari, Muhammad Ahsan; Zai, Sammer; Moon, Young Shik

2017-01-01

Manual analysis of the bulk data generated by computed tomography angiography (CTA) is time consuming, and interpretation of such data requires previous knowledge and expertise of the radiologist. Therefore, an automatic method that can isolate the coronary arteries from a given CTA dataset is required. We present an automatic yet effective segmentation method to delineate the coronary arteries from a three-dimensional CTA data cloud. Instead of a region growing process, which is usually time consuming and prone to leakages, the method is based on the optimal thresholding, which is applied globally on the Hessian-based vesselness measure in a localized way (slice by slice) to track the coronaries carefully to their distal ends. Moreover, to make the process automatic, we detect the aorta using the Hough transform technique. The proposed segmentation method is independent of the starting point to initiate its process and is fast in the sense that coronary arteries are obtained without any preprocessing or postprocessing steps. We used 12 real clinical datasets to show the efficiency and accuracy of the presented method. Experimental results reveal that the proposed method achieves 95% average accuracy.

Space Fabrication Demonstration System

NASA Technical Reports Server (NTRS)

1978-01-01

The completion of assembly of the beam builder and its first automatic production of truss is discussed. A four bay, hand assembled, roll formed members truss was built and tested to ultimate load. Detail design of the fabrication facility (beam builder) was completed and designs for subsystem debugging are discussed. Many one bay truss specimens were produced to demonstrate subsystem operation and to detect problem areas.

Phantom Study Investigating the Accuracy of Manual and Automatic Image Fusion with the GE Logiq E9: Implications for use in Percutaneous Liver Interventions.

PubMed

Burgmans, Mark Christiaan; den Harder, J Michiel; Meershoek, Philippa; van den Berg, Nynke S; Chan, Shaun Xavier Ju Min; van Leeuwen, Fijs W B; van Erkel, Arian R

2017-06-01

To determine the accuracy of automatic and manual co-registration methods for image fusion of three-dimensional computed tomography (CT) with real-time ultrasonography (US) for image-guided liver interventions. CT images of a skills phantom with liver lesions were acquired and co-registered to US using GE Logiq E9 navigation software. Manual co-registration was compared to automatic and semiautomatic co-registration using an active tracker. Also, manual point registration was compared to plane registration with and without an additional translation point. Finally, comparison was made between manual and automatic selection of reference points. In each experiment, accuracy of the co-registration method was determined by measurement of the residual displacement in phantom lesions by two independent observers. Mean displacements for a superficial and deep liver lesion were comparable after manual and semiautomatic co-registration: 2.4 and 2.0 mm versus 2.0 and 2.5 mm, respectively. Both methods were significantly better than automatic co-registration: 5.9 and 5.2 mm residual displacement (p < 0.001; p < 0.01). The accuracy of manual point registration was higher than that of plane registration, the latter being heavily dependent on accurate matching of axial CT and US images by the operator. Automatic reference point selection resulted in significantly lower registration accuracy compared to manual point selection despite lower root-mean-square deviation (RMSD) values. The accuracy of manual and semiautomatic co-registration is better than that of automatic co-registration. For manual co-registration using a plane, choosing the correct plane orientation is an essential first step in the registration process. Automatic reference point selection based on RMSD values is error-prone.

Automatic cloud tracking applied to GOES and Meteosat observations

NASA Technical Reports Server (NTRS)

Endlich, R. M.; Wolf, D. E.

1981-01-01

An improved automatic processing method for the tracking of cloud motions as revealed by satellite imagery is presented and applications of the method to GOES observations of Hurricane Eloise and Meteosat water vapor and infrared data are presented. The method is shown to involve steps of picture smoothing, target selection and the calculation of cloud motion vectors by the matching of a group at a given time with its best likeness at a later time, or by a cross-correlation computation. Cloud motion computations can be made in as many as four separate layers simultaneously. For data of 4 and 8 km resolution in the eye of Hurricane Eloise, the automatic system is found to provide results comparable in accuracy and coverage to those obtained by NASA analysts using the Atmospheric and Oceanographic Information Processing System, with results obtained by the pattern recognition and cross correlation computations differing by only fractions of a pixel. For Meteosat water vapor data from the tropics and midlatitudes, the automatic motion computations are found to be reliable only in areas where the water vapor fields contained small-scale structure, although excellent results are obtained using Meteosat IR data in the same regions. The automatic method thus appears to be competitive in accuracy and coverage with motion determination by human analysts.

Automatic blood vessel based-liver segmentation using the portal phase abdominal CT

NASA Astrophysics Data System (ADS)

Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Shimada, Mitsuo; Iinuma, Gen

2018-02-01

Liver segmentation is the basis for computer-based planning of hepatic surgical interventions. In diagnosis and analysis of hepatic diseases and surgery planning, automatic segmentation of liver has high importance. Blood vessel (BV) has showed high performance at liver segmentation. In our previous work, we developed a semi-automatic method that segments the liver through the portal phase abdominal CT images in two stages. First stage was interactive segmentation of abdominal blood vessels (ABVs) and subsequent classification into hepatic (HBVs) and non-hepatic (non-HBVs). This stage had 5 interactions that include selective threshold for bone segmentation, selecting two seed points for kidneys segmentation, selection of inferior vena cava (IVC) entrance for starting ABVs segmentation, identification of the portal vein (PV) entrance to the liver and the IVC-exit for classifying HBVs from other ABVs (non-HBVs). Second stage is automatic segmentation of the liver based on segmented ABVs as described in [4]. For full automation of our method we developed a method [5] that segments ABVs automatically tackling the first three interactions. In this paper, we propose full automation of classifying ABVs into HBVs and non- HBVs and consequently full automation of liver segmentation that we proposed in [4]. Results illustrate that the method is effective at segmentation of the liver through the portal abdominal CT images.

Automatic Coding of Short Text Responses via Clustering in Educational Assessment

ERIC Educational Resources Information Center

Zehner, Fabian; Sälzer, Christine; Goldhammer, Frank

2016-01-01

Automatic coding of short text responses opens new doors in assessment. We implemented and integrated baseline methods of natural language processing and statistical modelling by means of software components that are available under open licenses. The accuracy of automatic text coding is demonstrated by using data collected in the "Programme…

Automatic segmentation of relevant structures in DCE MR mammograms

NASA Astrophysics Data System (ADS)

Koenig, Matthias; Laue, Hendrik; Boehler, Tobias; Peitgen, Heinz-Otto

2007-03-01

The automatic segmentation of relevant structures such as skin edge, chest wall, or nipple in dynamic contrast enhanced MR imaging (DCE MRI) of the breast provides additional information for computer aided diagnosis (CAD) systems. Automatic reporting using BI-RADS criteria benefits of information about location of those structures. Lesion positions can be automatically described relatively to such reference structures for reporting purposes. Furthermore, this information can assist data reduction for computation expensive preprocessing such as registration, or for visualization of only the segments of current interest. In this paper, a novel automatic method for determining the air-breast boundary resp. skin edge, for approximation of the chest wall, and locating of the nipples is presented. The method consists of several steps which are built on top of each other. Automatic threshold computation leads to the air-breast boundary which is then analyzed to determine the location of the nipple. Finally, results of both steps are starting point for approximation of the chest wall. The proposed process was evaluated on a large data set of DCE MRI recorded by T1 sequences and yielded reasonable results in all cases.

Seeing the unseen: Complete volcano deformation fields by recursive filtering of satellite radar interferograms

NASA Astrophysics Data System (ADS)

Gonzalez, Pablo J.

2017-04-01

Automatic interferometric processing of satellite radar data has emerged as a solution to the increasing amount of acquired SAR data. Automatic SAR and InSAR processing ranges from focusing raw echoes to the computation of displacement time series using large stacks of co-registered radar images. However, this type of interferometric processing approach demands the pre-described or adaptive selection of multiple processing parameters. One of the interferometric processing steps that much strongly influences the final results (displacement maps) is the interferometric phase filtering. There are a large number of phase filtering methods, however the "so-called" Goldstein filtering method is the most popular [Goldstein and Werner, 1998; Baran et al., 2003]. The Goldstein filter needs basically two parameters, the size of the window filter and a parameter to indicate the filter smoothing intensity. The modified Goldstein method removes the need to select the smoothing parameter based on the local interferometric coherence level, but still requires to specify the dimension of the filtering window. An optimal filtered phase quality usually requires careful selection of those parameters. Therefore, there is an strong need to develop automatic filtering methods to adapt for automatic processing, while maximizing filtered phase quality. Here, in this paper, I present a recursive adaptive phase filtering algorithm for accurate estimation of differential interferometric ground deformation and local coherence measurements. The proposed filter is based upon the modified Goldstein filter [Baran et al., 2003]. This filtering method improves the quality of the interferograms by performing a recursive iteration using variable (cascade) kernel sizes, and improving the coherence estimation by locally defringing the interferometric phase. The method has been tested using simulations and real cases relevant to the characteristics of the Sentinel-1 mission. Here, I present real examples from C-band interferograms showing strong and weak deformation gradients, with moderate baselines ( 100-200 m) and variable temporal baselines of 70 and 190 days over variable vegetated volcanoes (Mt. Etna, Hawaii and Nyragongo-Nyamulagira). The differential phase of those examples show intense localized volcano deformation and also vast areas of small differential phase variation. The proposed method outperforms the classical Goldstein and modified Goldstein filters by preserving subtle phase variations where the deformation fringe rate is high, and effectively suppressing phase noise in smoothly phase variation regions. Finally, this method also has the additional advantage of not requiring input parameters, except for the maximum filtering kernel size. References: Baran, I., Stewart, M.P., Kampes, B.M., Perski, Z., Lilly, P., (2003) A modification to the Goldstein radar interferogram filter. IEEE Transactions on Geoscience and Remote Sensing, vol. 41, No. 9., doi:10.1109/TGRS.2003.817212 Goldstein, R.M., Werner, C.L. (1998) Radar interferogram filtering for geophysical applications, Geophysical Research Letters, vol. 25, No. 21, 4035-4038, doi:10.1029/1998GL900033

User Interaction in Semi-Automatic Segmentation of Organs at Risk: a Case Study in Radiotherapy.

PubMed

Ramkumar, Anjana; Dolz, Jose; Kirisli, Hortense A; Adebahr, Sonja; Schimek-Jasch, Tanja; Nestle, Ursula; Massoptier, Laurent; Varga, Edit; Stappers, Pieter Jan; Niessen, Wiro J; Song, Yu

2016-04-01

Accurate segmentation of organs at risk is an important step in radiotherapy planning. Manual segmentation being a tedious procedure and prone to inter- and intra-observer variability, there is a growing interest in automated segmentation methods. However, automatic methods frequently fail to provide satisfactory result, and post-processing corrections are often needed. Semi-automatic segmentation methods are designed to overcome these problems by combining physicians' expertise and computers' potential. This study evaluates two semi-automatic segmentation methods with different types of user interactions, named the "strokes" and the "contour", to provide insights into the role and impact of human-computer interaction. Two physicians participated in the experiment. In total, 42 case studies were carried out on five different types of organs at risk. For each case study, both the human-computer interaction process and quality of the segmentation results were measured subjectively and objectively. Furthermore, different measures of the process and the results were correlated. A total of 36 quantifiable and ten non-quantifiable correlations were identified for each type of interaction. Among those pairs of measures, 20 of the contour method and 22 of the strokes method were strongly or moderately correlated, either directly or inversely. Based on those correlated measures, it is concluded that: (1) in the design of semi-automatic segmentation methods, user interactions need to be less cognitively challenging; (2) based on the observed workflows and preferences of physicians, there is a need for flexibility in the interface design; (3) the correlated measures provide insights that can be used in improving user interaction design.

Quality assurance using outlier detection on an automatic segmentation method for the cerebellar peduncles

NASA Astrophysics Data System (ADS)

Li, Ke; Ye, Chuyang; Yang, Zhen; Carass, Aaron; Ying, Sarah H.; Prince, Jerry L.

2016-03-01

Cerebellar peduncles (CPs) are white matter tracts connecting the cerebellum to other brain regions. Automatic segmentation methods of the CPs have been proposed for studying their structure and function. Usually the performance of these methods is evaluated by comparing segmentation results with manual delineations (ground truth). However, when a segmentation method is run on new data (for which no ground truth exists) it is highly desirable to efficiently detect and assess algorithm failures so that these cases can be excluded from scientific analysis. In this work, two outlier detection methods aimed to assess the performance of an automatic CP segmentation algorithm are presented. The first one is a univariate non-parametric method using a box-whisker plot. We first categorize automatic segmentation results of a dataset of diffusion tensor imaging (DTI) scans from 48 subjects as either a success or a failure. We then design three groups of features from the image data of nine categorized failures for failure detection. Results show that most of these features can efficiently detect the true failures. The second method—supervised classification—was employed on a larger DTI dataset of 249 manually categorized subjects. Four classifiers—linear discriminant analysis (LDA), logistic regression (LR), support vector machine (SVM), and random forest classification (RFC)—were trained using the designed features and evaluated using a leave-one-out cross validation. Results show that the LR performs worst among the four classifiers and the other three perform comparably, which demonstrates the feasibility of automatically detecting segmentation failures using classification methods.

Matrix Completion Optimization for Localization in Wireless Sensor Networks for Intelligent IoT

PubMed Central

Nguyen, Thu L. N.; Shin, Yoan

2016-01-01

Localization in wireless sensor networks (WSNs) is one of the primary functions of the intelligent Internet of Things (IoT) that offers automatically discoverable services, while the localization accuracy is a key issue to evaluate the quality of those services. In this paper, we develop a framework to solve the Euclidean distance matrix completion problem, which is an important technical problem for distance-based localization in WSNs. The sensor network localization problem is described as a low-rank dimensional Euclidean distance completion problem with known nodes. The task is to find the sensor locations through recovery of missing entries of a squared distance matrix when the dimension of the data is small compared to the number of data points. We solve a relaxation optimization problem using a modification of Newton’s method, where the cost function depends on the squared distance matrix. The solution obtained in our scheme achieves a lower complexity and can perform better if we use it as an initial guess for an interactive local search of other higher precision localization scheme. Simulation results show the effectiveness of our approach. PMID:27213378

Simulator training to automaticity leads to improved skill transfer compared with traditional proficiency-based training: a randomized controlled trial.

PubMed

Stefanidis, Dimitrios; Scerbo, Mark W; Montero, Paul N; Acker, Christina E; Smith, Warren D

2012-01-01

We hypothesized that novices will perform better in the operating room after simulator training to automaticity compared with traditional proficiency based training (current standard training paradigm). Simulator-acquired skill translates to the operating room, but the skill transfer is incomplete. Secondary task metrics reflect the ability of trainees to multitask (automaticity) and may improve performance assessment on simulators and skill transfer by indicating when learning is complete. Novices (N = 30) were enrolled in an IRB-approved, blinded, randomized, controlled trial. Participants were randomized into an intervention (n = 20) and a control (n = 10) group. The intervention group practiced on the FLS suturing task until they achieved expert levels of time and errors (proficiency), were tested on a live porcine fundoplication model, continued simulator training until they achieved expert levels on a visual spatial secondary task (automaticity) and were retested on the operating room (OR) model. The control group participated only during testing sessions. Performance scores were compared within and between groups during testing sessions. : Intervention group participants achieved proficiency after 54 ± 14 and automaticity after additional 109 ± 57 repetitions. Participants achieved better scores in the OR after automaticity training [345 (range, 0-537)] compared with after proficiency-based training [220 (range, 0-452; P < 0.001]. Simulator training to automaticity takes more time but is superior to proficiency-based training, as it leads to improved skill acquisition and transfer. Secondary task metrics that reflect trainee automaticity should be implemented during simulator training to improve learning and skill transfer.

Reliable clarity automatic-evaluation method for optical remote sensing images

NASA Astrophysics Data System (ADS)

Qin, Bangyong; Shang, Ren; Li, Shengyang; Hei, Baoqin; Liu, Zhiwen

2015-10-01

Image clarity, which reflects the sharpness degree at the edge of objects in images, is an important quality evaluate index for optical remote sensing images. Scholars at home and abroad have done a lot of work on estimation of image clarity. At present, common clarity-estimation methods for digital images mainly include frequency-domain function methods, statistical parametric methods, gradient function methods and edge acutance methods. Frequency-domain function method is an accurate clarity-measure approach. However, its calculation process is complicate and cannot be carried out automatically. Statistical parametric methods and gradient function methods are both sensitive to clarity of images, while their results are easy to be affected by the complex degree of images. Edge acutance method is an effective approach for clarity estimate, while it needs picking out the edges manually. Due to the limits in accuracy, consistent or automation, these existing methods are not applicable to quality evaluation of optical remote sensing images. In this article, a new clarity-evaluation method, which is based on the principle of edge acutance algorithm, is proposed. In the new method, edge detection algorithm and gradient search algorithm are adopted to automatically search the object edges in images. Moreover, The calculation algorithm for edge sharpness has been improved. The new method has been tested with several groups of optical remote sensing images. Compared with the existing automatic evaluation methods, the new method perform better both in accuracy and consistency. Thus, the new method is an effective clarity evaluation method for optical remote sensing images.

Improve accuracy for automatic acetabulum segmentation in CT images.

PubMed

Liu, Hao; Zhao, Jianning; Dai, Ning; Qian, Hongbo; Tang, Yuehong

2014-01-01

Separation of the femur head and acetabulum is one of main difficulties in the diseased hip joint due to deformed shapes and extreme narrowness of the joint space. To improve the segmentation accuracy is the key point of existing automatic or semi-automatic segmentation methods. In this paper, we propose a new method to improve the accuracy of the segmented acetabulum using surface fitting techniques, which essentially consists of three parts: (1) design a surface iterative process to obtain an optimization surface; (2) change the ellipsoid fitting to two-phase quadric surface fitting; (3) bring in a normal matching method and an optimization region method to capture edge points for the fitting quadric surface. Furthermore, this paper cited vivo CT data sets of 40 actual patients (with 79 hip joints). Test results for these clinical cases show that: (1) the average error of the quadric surface fitting method is 2.3 (mm); (2) the accuracy ratio of automatically recognized contours is larger than 89.4%; (3) the error ratio of section contours is less than 10% for acetabulums without severe malformation and less than 30% for acetabulums with severe malformation. Compared with similar methods, the accuracy of our method, which is applied in a software system, is significantly enhanced.

Finite element modelling and updating of a lively footbridge: The complete process

NASA Astrophysics Data System (ADS)

Živanović, Stana; Pavic, Aleksandar; Reynolds, Paul

2007-03-01

The finite element (FE) model updating technology was originally developed in the aerospace and mechanical engineering disciplines to automatically update numerical models of structures to match their experimentally measured counterparts. The process of updating identifies the drawbacks in the FE modelling and the updated FE model could be used to produce more reliable results in further dynamic analysis. In the last decade, the updating technology has been introduced into civil structural engineering. It can serve as an advanced tool for getting reliable modal properties of large structures. The updating process has four key phases: initial FE modelling, modal testing, manual model tuning and automatic updating (conducted using specialist software). However, the published literature does not connect well these phases, although this is crucial when implementing the updating technology. This paper therefore aims to clarify the importance of this linking and to describe the complete model updating process as applicable in civil structural engineering. The complete process consisting the four phases is outlined and brief theory is presented as appropriate. Then, the procedure is implemented on a lively steel box girder footbridge. It was found that even a very detailed initial FE model underestimated the natural frequencies of all seven experimentally identified modes of vibration, with the maximum error being almost 30%. Manual FE model tuning by trial and error found that flexible supports in the longitudinal direction should be introduced at the girder ends to improve correlation between the measured and FE-calculated modes. This significantly reduced the maximum frequency error to only 4%. It was demonstrated that only then could the FE model be automatically updated in a meaningful way. The automatic updating was successfully conducted by updating 22 uncertain structural parameters. Finally, a physical interpretation of all parameter changes is discussed. This interpretation is often missing in the published literature. It was found that the composite slabs were less stiff than originally assumed and that the asphalt layer contributed considerably to the deck stiffness.

An automatically updateable web publishing solution: taking document sharing and conversion to enterprise level

NASA Astrophysics Data System (ADS)

Rahman, Fuad; Tarnikova, Yuliya; Hartono, Rachmat; Alam, Hassan

2006-01-01

This paper presents a novel automatic web publishing solution, Pageview (R). PageView (R) is a complete working solution for document processing and management. The principal aim of this tool is to allow workgroups to share, access and publish documents on-line on a regular basis. For example, assuming that a person is working on some documents. The user will, in some fashion, organize his work either in his own local directory or in a shared network drive. Now extend that concept to a workgroup. Within a workgroup, some users are working together on some documents, and they are saving them in a directory structure somewhere on a document repository. The next stage of this reasoning is that a workgroup is working on some documents, and they want to publish them routinely on-line. Now it may happen that they are using different editing tools, different software, and different graphics tools. The resultant documents may be in PDF, Microsoft Office (R), HTML, or Word Perfect format, just to name a few. In general, this process needs the documents to be processed in a fashion so that they are in the HTML format, and then a web designer needs to work on that collection to make them available on-line. PageView (R) takes care of this whole process automatically, making the document workflow clean and easy to follow. PageView (R) Server publishes documents, complete with the directory structure, for online use. The documents are automatically converted to HTML and PDF so that users can view the content without downloading the original files, or having to download browser plug-ins. Once published, other users can access the documents as if they are accessing them from their local folders. The paper will describe the complete working system and will discuss possible applications within the document management research.

Study on digital teeth selection and virtual teeth arrangement for complete denture.

PubMed

Yu, Xiaoling; Cheng, Xiaosheng; Dai, Ning; Chen, Hu; Yu, Changjiang; Sun, Yuchun

2018-03-01

In dentistry, the complete denture is a conventional treatment for edentulous patients. The computer-aided design and computer-aided manufacturing (CAD/CAM) has been applied on the digital complete denture which is developed rapidly. Tooth selection and arrangement is one of the most important parts in digital complete denture. In this paper, we propose a new method of personalized teeth arrangement. This paper presents a method of arranging teeth virtually for a complete denture. First, scan and extract the feature points of the 3D triangular mesh data of artificial teeth (PLY format), then establish a tooth selection system. Second, scan and mark the anatomic characteristics of the maxillary and mandibular cast surfaces, such as facial midline, the curve of the arches. With the enter information, the study calculates the common arrangement lines of artificial teeth. Third, select the preferred artificial teeth and automatically arrange them virtually in the correct position by using our own software. After that, design the gingival part of the dentures on the basic of the arranged teeth on the screen and then fabricated it by using Computerized Numerical Control (CNC) technology, Rapid Prototyping (RP) technology or 3D printer technology. Finally, select artificial teeth were embedded in wax rims. This system can choose artificial teeth reasonably and the teeth placement can meet the dentist's request to a certain extent, whereas all the operations are based on the medical principles. The study performed here involves computer sciences, medicine, and dentistry, a teeth selection system was proposed and virtual teeth arrangement was described. This study has the capacity of helping operators to select teeth, which improved the accuracy of tooth arrangement, and customized complete denture. Copyright © 2017 Elsevier B.V. All rights reserved.

Automatic detection of axillary lymphadenopathy on CT scans of untreated chronic lymphocytic leukemia patients

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Hua, Jeremy; Chellappa, Vivek; Petrick, Nicholas; Sahiner, Berkman; Farooqui, Mohammed; Marti, Gerald; Wiestner, Adrian; Summers, Ronald M.

2012-03-01

Patients with chronic lymphocytic leukemia (CLL) have an increased frequency of axillary lymphadenopathy. Pretreatment CT scans can be used to upstage patients at the time of presentation and post-treatment CT scans can reduce the number of complete responses. In the current clinical workflow, the detection and diagnosis of lymph nodes is usually performed manually by examining all slices of CT images, which can be time consuming and highly dependent on the observer's experience. A system for automatic lymph node detection and measurement is desired. We propose a computer aided detection (CAD) system for axillary lymph nodes on CT scans in CLL patients. The lung is first automatically segmented and the patient's body in lung region is extracted to set the search region for lymph nodes. Multi-scale Hessian based blob detection is then applied to detect potential lymph nodes within the search region. Next, the detected potential candidates are segmented by fast level set method. Finally, features are calculated from the segmented candidates and support vector machine (SVM) classification is utilized for false positive reduction. Two blobness features, Frangi's and Li's, are tested and their free-response receiver operating characteristic (FROC) curves are generated to assess system performance. We applied our detection system to 12 patients with 168 axillary lymph nodes measuring greater than 10 mm. All lymph nodes are manually labeled as ground truth. The system achieved sensitivities of 81% and 85% at 2 false positives per patient for Frangi's and Li's blobness, respectively.

Phase coherence adaptive processor for automatic signal detection and identification

NASA Astrophysics Data System (ADS)

Wagstaff, Ronald A.

2006-05-01

A continuously adapting acoustic signal processor with an automatic detection/decision aid is presented. Its purpose is to preserve the signals of tactical interest, and filter out other signals and noise. It utilizes single sensor or beamformed spectral data and transforms the signal and noise phase angles into "aligned phase angles" (APA). The APA increase the phase temporal coherence of signals and leave the noise incoherent. Coherence thresholds are set, which are representative of the type of source "threat vehicle" and the geographic area or volume in which it is operating. These thresholds separate signals, based on the "quality" of their APA coherence. An example is presented in which signals from a submerged source in the ocean are preserved, while clutter signals from ships and noise are entirely eliminated. Furthermore, the "signals of interest" were identified by the processor's automatic detection aid. Similar performance is expected for air and ground vehicles. The processor's equations are formulated in such a manner that they can be tuned to eliminate noise and exploit signal, based on the "quality" of their APA temporal coherence. The mathematical formulation for this processor is presented, including the method by which the processor continuously self-adapts. Results show nearly complete elimination of noise, with only the selected category of signals remaining, and accompanying enhancements in spectral and spatial resolution. In most cases, the concept of signal-to-noise ratio looses significance, and "adaptive automated /decision aid" is more relevant.

Automated high-performance cIMT measurement techniques using patented AtheroEdge™: a screening and home monitoring system.

PubMed

Molinari, Filippo; Meiburger, Kristen M; Suri, Jasjit

2011-01-01

The evaluation of the carotid artery wall is fundamental for the assessment of cardiovascular risk. This paper presents the general architecture of an automatic strategy, which segments the lumen-intima and media-adventitia borders, classified under a class of Patented AtheroEdge™ systems (Global Biomedical Technologies, Inc, CA, USA). Guidelines to produce accurate and repeatable measurements of the intima-media thickness are provided and the problem of the different distance metrics one can adopt is confronted. We compared the results of a completely automatic algorithm that we developed with those of a semi-automatic algorithm, and showed final segmentation results for both techniques. The overall rationale is to provide user-independent high-performance techniques suitable for screening and remote monitoring.

DiTour 3.1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pelaia II, Thomas A.

2015-06-30

There is a need for software that allows a tour guide to present different tracks of slides and then return to the default slide show automatically upon completion. A mobile solution is needed for trade shows. DiTour is an iPad/iPhone app that pulls presentation content from a website, stores it on the device and presents it on a connected display. A tour guide can select a track to present and it will automatically return to the default track after a timeout. It offers a mobile solution which is ideal for trade shows.

Automatic short axis orientation of the left ventricle in 3D ultrasound recordings

NASA Astrophysics Data System (ADS)

Pedrosa, João.; Heyde, Brecht; Heeren, Laurens; Engvall, Jan; Zamorano, Jose; Papachristidis, Alexandros; Edvardsen, Thor; Claus, Piet; D'hooge, Jan

2016-04-01

The recent advent of three-dimensional echocardiography has led to an increased interest from the scientific community in left ventricle segmentation frameworks for cardiac volume and function assessment. An automatic orientation of the segmented left ventricular mesh is an important step to obtain a point-to-point correspondence between the mesh and the cardiac anatomy. Furthermore, this would allow for an automatic division of the left ventricle into the standard 17 segments and, thus, fully automatic per-segment analysis, e.g. regional strain assessment. In this work, a method for fully automatic short axis orientation of the segmented left ventricle is presented. The proposed framework aims at detecting the inferior right ventricular insertion point. 211 three-dimensional echocardiographic images were used to validate this framework by comparison to manual annotation of the inferior right ventricular insertion point. A mean unsigned error of 8, 05° +/- 18, 50° was found, whereas the mean signed error was 1, 09°. Large deviations between the manual and automatic annotations (> 30°) only occurred in 3, 79% of cases. The average computation time was 666ms in a non-optimized MATLAB environment, which potentiates real-time application. In conclusion, a successful automatic real-time method for orientation of the segmented left ventricle is proposed.

Validation of automatic landmark identification for atlas-based segmentation for radiation treatment planning of the head-and-neck region

NASA Astrophysics Data System (ADS)

Leavens, Claudia; Vik, Torbjørn; Schulz, Heinrich; Allaire, Stéphane; Kim, John; Dawson, Laura; O'Sullivan, Brian; Breen, Stephen; Jaffray, David; Pekar, Vladimir

2008-03-01

Manual contouring of target volumes and organs at risk in radiation therapy is extremely time-consuming, in particular for treating the head-and-neck area, where a single patient treatment plan can take several hours to contour. As radiation treatment delivery moves towards adaptive treatment, the need for more efficient segmentation techniques will increase. We are developing a method for automatic model-based segmentation of the head and neck. This process can be broken down into three main steps: i) automatic landmark identification in the image dataset of interest, ii) automatic landmark-based initialization of deformable surface models to the patient image dataset, and iii) adaptation of the deformable models to the patient-specific anatomical boundaries of interest. In this paper, we focus on the validation of the first step of this method, quantifying the results of our automatic landmark identification method. We use an image atlas formed by applying thin-plate spline (TPS) interpolation to ten atlas datasets, using 27 manually identified landmarks in each atlas/training dataset. The principal variation modes returned by principal component analysis (PCA) of the landmark positions were used by an automatic registration algorithm, which sought the corresponding landmarks in the clinical dataset of interest using a controlled random search algorithm. Applying a run time of 60 seconds to the random search, a root mean square (rms) distance to the ground-truth landmark position of 9.5 +/- 0.6 mm was calculated for the identified landmarks. Automatic segmentation of the brain, mandible and brain stem, using the detected landmarks, is demonstrated.

Optic cup segmentation from fundus images for glaucoma diagnosis.

PubMed

Hu, Man; Zhu, Chenghao; Li, Xiaoxing; Xu, Yongli

2017-01-02

Glaucoma is a serious disease that can cause complete, permanent blindness, and its early diagnosis is very difficult. In recent years, computer-aided screening and diagnosis of glaucoma has made considerable progress. The optic cup segmentation from fundus images is an extremely important part for the computer-aided screening and diagnosis of glaucoma. This paper presented an automatic optic cup segmentation method that used both color difference information and vessel bends information from fundus images to determine the optic cup boundary. During the implementation of this algorithm, not only were the locations of the 2 types of information points used, but also the confidences of the information points were evaluated. In this way, the information points with higher confidence levels contributed more to the determination of the final cup boundary. The proposed method was evaluated using a public database for fundus images. The experimental results demonstrated that the cup boundaries obtained by the proposed method were more consistent than existing methods with the results obtained by ophthalmologists.

Automated structure determination of proteins with the SAIL-FLYA NMR method.

PubMed

Takeda, Mitsuhiro; Ikeya, Teppei; Güntert, Peter; Kainosho, Masatsune

2007-01-01

The labeling of proteins with stable isotopes enhances the NMR method for the determination of 3D protein structures in solution. Stereo-array isotope labeling (SAIL) provides an optimal stereospecific and regiospecific pattern of stable isotopes that yields sharpened lines, spectral simplification without loss of information, and the ability to collect rapidly and evaluate fully automatically the structural restraints required to solve a high-quality solution structure for proteins up to twice as large as those that can be analyzed using conventional methods. Here, we describe a protocol for the preparation of SAIL proteins by cell-free methods, including the preparation of S30 extract and their automated structure analysis using the FLYA algorithm and the program CYANA. Once efficient cell-free expression of the unlabeled or uniformly labeled target protein has been achieved, the NMR sample preparation of a SAIL protein can be accomplished in 3 d. A fully automated FLYA structure calculation can be completed in 1 d on a powerful computer system.

Optic cup segmentation from fundus images for glaucoma diagnosis

PubMed Central

Hu, Man; Zhu, Chenghao; Li, Xiaoxing; Xu, Yongli

2017-01-01

ABSTRACT Glaucoma is a serious disease that can cause complete, permanent blindness, and its early diagnosis is very difficult. In recent years, computer-aided screening and diagnosis of glaucoma has made considerable progress. The optic cup segmentation from fundus images is an extremely important part for the computer-aided screening and diagnosis of glaucoma. This paper presented an automatic optic cup segmentation method that used both color difference information and vessel bends information from fundus images to determine the optic cup boundary. During the implementation of this algorithm, not only were the locations of the 2 types of information points used, but also the confidences of the information points were evaluated. In this way, the information points with higher confidence levels contributed more to the determination of the final cup boundary. The proposed method was evaluated using a public database for fundus images. The experimental results demonstrated that the cup boundaries obtained by the proposed method were more consistent than existing methods with the results obtained by ophthalmologists. PMID:27764542

Automatic Derivation of Forest Cover and Forest Cover Change Using Dense Multi-Temporal Time Series Data from Landsat and SPOT 5 Take5

NASA Astrophysics Data System (ADS)

Storch, Cornelia; Wagner, Thomas; Ramminger, Gernot; Pape, Marlon; Ott, Hannes; Hausler, Thomas; Gomez, Sharon

2016-08-01

The paper presents a description of the methods development for an automated processing chain for the classification of Forest Cover and Change based on high resolution multi-temporal time series Landsat and SPOT5Take5 data with focus on the dry forest ecosystems of Africa. The method has been developed within the European Space Agency (ESA) funded Global monitoring for Environment and Security Service Element for Forest Monitoring (GSE FM) project on dry forest areas; the demonstration site selected was in Malawi. The methods are based on the principles of a robust, but still flexible monitoring system, to cope with most complex Earth Observation (EO) data scenarios, varying in terms of data quality, source, accuracy, information content, completeness etc. The method allows automated tracking of change dates, data gap filling and takes into account phenology, seasonality of tree species with respect to leaf fall and heavy cloud cover during the rainy season.

A comparison of different methods to implement higher order derivatives of density functionals

DOE Office of Scientific and Technical Information (OSTI.GOV)

van Dam, Hubertus J.J.

Density functional theory is the dominant approach in electronic structure methods today. To calculate properties higher order derivatives of the density functionals are required. These derivatives might be implemented manually,by automatic differentiation, or by symbolic algebra programs. Different authors have cited different reasons for using the particular method of their choice. This paper presents work where all three approaches were used and the strengths and weaknesses of each approach are considered. It is found that all three methods produce code that is suffficiently performanted for practical applications, despite the fact that our symbolic algebra generated code and our automatic differentiationmore » code still have scope for significant optimization. The automatic differentiation approach is the best option for producing readable and maintainable code.« less

High definition for systems biology of microbial communities: metagenomics gets genome-centric and strain-resolved.

PubMed

Turaev, Dmitrij; Rattei, Thomas

2016-06-01

The systems biology of microbial communities, organismal communities inhabiting all ecological niches on earth, has in recent years been strongly facilitated by the rapid development of experimental, sequencing and data analysis methods. Novel experimental approaches and binning methods in metagenomics render the semi-automatic reconstructions of near-complete genomes of uncultivable bacteria possible, while advances in high-resolution amplicon analysis allow for efficient and less biased taxonomic community characterization. This will also facilitate predictive modeling approaches, hitherto limited by the low resolution of metagenomic data. In this review, we pinpoint the most promising current developments in metagenomics. They facilitate microbial systems biology towards a systemic understanding of mechanisms in microbial communities with scopes of application in many areas of our daily life. Copyright © 2016 Elsevier Ltd. All rights reserved.

Structured filtering

NASA Astrophysics Data System (ADS)

Granade, Christopher; Wiebe, Nathan

2017-08-01

A major challenge facing existing sequential Monte Carlo methods for parameter estimation in physics stems from the inability of existing approaches to robustly deal with experiments that have different mechanisms that yield the results with equivalent probability. We address this problem here by proposing a form of particle filtering that clusters the particles that comprise the sequential Monte Carlo approximation to the posterior before applying a resampler. Through a new graphical approach to thinking about such models, we are able to devise an artificial-intelligence based strategy that automatically learns the shape and number of the clusters in the support of the posterior. We demonstrate the power of our approach by applying it to randomized gap estimation and a form of low circuit-depth phase estimation where existing methods from the physics literature either exhibit much worse performance or even fail completely.

Separation and identification of neutral cereal lipids by normal phase high-performance liquid chromatography, using evaporative light-scattering and electrospray mass spectrometry for detection.

PubMed

Rocha, João M; Kalo, Paavo J; Ollilainen, Velimatti; Malcata, F Xavier

2010-04-30

A novel method was developed for the analysis of molecular species in neutral lipid classes, using separation by normal phase high-performance liquid chromatography, followed by detection by evaporative light-scattering and electrospray ionization tandem mass spectrometry. Monoacid standards, i.e. sterol esters, triacylglycerols, fatty acids, diacylglycerols, free sterols and monoacylglycerols, were separated to baseline on microbore 3 microm-silica gel columns. Complete or partial separation of molecular species in each lipid class permitted identification by automatic tandem mass spectrometry of ammonium adducts, produced via positive electrospray ionization. After optimization of the method, separation and identification of molecular species of various lipid classes was comprehensively tested by analysis of neutral lipids from the free lipid extract of maize flour. 2010 Elsevier B.V. All rights reserved.

Brain Tumor Image Segmentation in MRI Image

NASA Astrophysics Data System (ADS)

Peni Agustin Tjahyaningtijas, Hapsari

2018-04-01

Brain tumor segmentation plays an important role in medical image processing. Treatment of patients with brain tumors is highly dependent on early detection of these tumors. Early detection of brain tumors will improve the patient’s life chances. Diagnosis of brain tumors by experts usually use a manual segmentation that is difficult and time consuming because of the necessary automatic segmentation. Nowadays automatic segmentation is very populer and can be a solution to the problem of tumor brain segmentation with better performance. The purpose of this paper is to provide a review of MRI-based brain tumor segmentation methods. There are number of existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation. this paper, we focus on the recent trend of automatic segmentation in this field. First, an introduction to brain tumors and methods for brain tumor segmentation is given. Then, the state-of-the-art algorithms with a focus on recent trend of full automatic segmentaion are discussed. Finally, an assessment of the current state is presented and future developments to standardize MRI-based brain tumor segmentation methods into daily clinical routine are addressed.

What is automatized during perceptual categorization?

PubMed Central

Roeder, Jessica L.; Ashby, F. Gregory

2016-01-01

An experiment is described that tested whether stimulus-response associations or an abstract rule are automatized during extensive practice at perceptual categorization. Twenty-seven participants each completed 12,300 trials of perceptual categorization, either on rule-based (RB) categories that could be learned explicitly or information-integration (II) categories that required procedural learning. Each participant practiced predominantly on a primary category structure, but every third session they switched to a secondary structure that used the same stimuli and responses. Half the stimuli retained their same response on the primary and secondary categories (the congruent stimuli) and half switched responses (the incongruent stimuli). Several results stood out. First, performance on the primary categories met the standard criteria of automaticity by the end of training. Second, for the primary categories in the RB condition, accuracy and response time (RT) were identical on congruent and incongruent stimuli. In contrast, for the primary II categories, accuracy was higher and RT was lower for congruent than for incongruent stimuli. These results are consistent with the hypothesis that rules are automatized in RB tasks, whereas stimulus-response associations are automatized in II tasks. A cognitive neuroscience theory is proposed that accounts for these results. PMID:27232521

A self-adapting heuristic for automatically constructing terrain appreciation exercises

NASA Astrophysics Data System (ADS)

Nanda, S.; Lickteig, C. L.; Schaefer, P. S.

2008-04-01

Appreciating terrain is a key to success in both symmetric and asymmetric forms of warfare. Training to enable Soldiers to master this vital skill has traditionally required their translocation to a selected number of areas, each affording a desired set of topographical features, albeit with limited breadth of variety. As a result, the use of such methods has proved to be costly and time consuming. To counter this, new computer-aided training applications permit users to rapidly generate and complete training exercises in geo-specific open and urban environments rendered by high-fidelity image generation engines. The latter method is not only cost-efficient, but allows any given exercise and its conditions to be duplicated or systematically varied over time. However, even such computer-aided applications have shortcomings. One of the principal ones is that they usually require all training exercises to be painstakingly constructed by a subject matter expert. Furthermore, exercise difficulty is usually subjectively assessed and frequently ignored thereafter. As a result, such applications lack the ability to grow and adapt to the skill level and learning curve of each trainee. In this paper, we present a heuristic that automatically constructs exercises for identifying key terrain. Each exercise is created and administered in a unique iteration, with its level of difficulty tailored to the trainee's ability based on the correctness of that trainee's responses in prior iterations.

Mission Connect Mild TBI Translational Research Consortium

DTIC Science & Technology

2013-08-01

year 2 and 3 annual progress report we completed the morphometric and the diffusion tensor imaging (DTI) in cortical impact injury with and without...and morphometric measures. Response to EAB feedback: No concerns were expressed by the External Advisory Board about the MRI core. Manuscript...automatic analysis of morphometry, DTI, and MTR for both humans and rodents.  Completed morphometric and DTI analysis in traumatically injured animals

Higher-order automatic differentiation of mathematical functions

NASA Astrophysics Data System (ADS)

Charpentier, Isabelle; Dal Cappello, Claude

2015-04-01

Functions of mathematical physics such as the Bessel functions, the Chebyshev polynomials, the Gauss hypergeometric function and so forth, have practical applications in many scientific domains. On the one hand, differentiation formulas provided in reference books apply to real or complex variables. These do not account for the chain rule. On the other hand, based on the chain rule, the automatic differentiation has become a natural tool in numerical modeling. Nevertheless automatic differentiation tools do not deal with the numerous mathematical functions. This paper describes formulas and provides codes for the higher-order automatic differentiation of mathematical functions. The first method is based on Faà di Bruno's formula that generalizes the chain rule. The second one makes use of the second order differential equation they satisfy. Both methods are exemplified with the aforementioned functions.

The unbalanced signal measuring of automotive brake drum

NASA Astrophysics Data System (ADS)

Wang, Xiao-Dong; Ye, Sheng-Hua; Zhang, Bang-Cheng

2005-04-01

For the purpose of the research and development of automatic balancing system by mass removing, the dissertation deals with the measuring method of the unbalance signal, the design the automatic balance equipment and the software. This paper emphases the testing system of the balancer of automotive brake drum. The paper designs the band-pass filter product with favorable automatic follow of electronic product, and with favorable automatic follow capability, filtration effect and stability. The system of automatic balancing system by mass removing based on virtual instrument is designed in this paper. A lab system has been constructed. The results of contrast experiments indicate the notable effect of 1-plane automatic balance and the high precision of dynamic balance, and demonstrate the application value of the system.

Automatic construction of subject-specific human airway geometry including trifurcations based on a CT-segmented airway skeleton and surface

PubMed Central

Miyawaki, Shinjiro; Tawhai, Merryn H.; Hoffman, Eric A.; Wenzel, Sally E.; Lin, Ching-Long

2016-01-01

We propose a method to construct three-dimensional airway geometric models based on airway skeletons, or centerlines (CLs). Given a CT-segmented airway skeleton and surface, the proposed CL-based method automatically constructs subject-specific models that contain anatomical information regarding branches, include bifurcations and trifurcations, and extend from the trachea to terminal bronchioles. The resulting model can be anatomically realistic with the assistance of an image-based surface; alternatively a model with an idealized skeleton and/or branch diameters is also possible. This method systematically identifies and classifies trifurcations to successfully construct the models, which also provides the number and type of trifurcations for the analysis of the airways from an anatomical point of view. We applied this method to 16 normal and 16 severe asthmatic subjects using their computed tomography images. The average distance between the surface of the model and the image-based surface was 11% of the average voxel size of the image. The four most frequent locations of trifurcations were the left upper division bronchus, left lower lobar bronchus, right upper lobar bronchus, and right intermediate bronchus. The proposed method automatically constructed accurate subject-specific three-dimensional airway geometric models that contain anatomical information regarding branches using airway skeleton, diameters, and image-based surface geometry. The proposed method can construct (i) geometry automatically for population-based studies, (ii) trifurcations to retain the original airway topology, (iii) geometry that can be used for automatic generation of computational fluid dynamics meshes, and (iv) geometry based only on a skeleton and diameters for idealized branches. PMID:27704229

CAD-based Automatic Modeling Method for Geant4 geometry model Through MCAM

NASA Astrophysics Data System (ADS)

Wang, Dong; Nie, Fanzhi; Wang, Guozhong; Long, Pengcheng; LV, Zhongliang; LV, Zhongliang

2014-06-01

Geant4 is a widely used Monte Carlo transport simulation package. Before calculating using Geant4, the calculation model need be established which could be described by using Geometry Description Markup Language (GDML) or C++ language. However, it is time-consuming and error-prone to manually describe the models by GDML. Automatic modeling methods have been developed recently, but there are some problem existed in most of present modeling programs, specially some of them were not accurate or adapted to specifically CAD format. To convert the GDML format models to CAD format accurately, a Geant4 Computer Aided Design (CAD) based modeling method was developed for automatically converting complex CAD geometry model into GDML geometry model. The essence of this method was dealing with CAD model represented with boundary representation (B-REP) and GDML model represented with constructive solid geometry (CSG). At first, CAD model was decomposed to several simple solids which had only one close shell. And then the simple solid was decomposed to convex shell set. Then corresponding GDML convex basic solids were generated by the boundary surfaces getting from the topological characteristic of a convex shell. After the generation of these solids, GDML model was accomplished with series boolean operations. This method was adopted in CAD/Image-based Automatic Modeling Program for Neutronics & Radiation Transport (MCAM), and tested with several models including the examples in Geant4 install package. The results showed that this method could convert standard CAD model accurately, and can be used for Geant4 automatic modeling.

Systems and methods for data quality control and cleansing

DOEpatents

Wenzel, Michael; Boettcher, Andrew; Drees, Kirk; Kummer, James

2016-05-31

A method for detecting and cleansing suspect building automation system data is shown and described. The method includes using processing electronics to automatically determine which of a plurality of error detectors and which of a plurality of data cleansers to use with building automation system data. The method further includes using processing electronics to automatically detect errors in the data and cleanse the data using a subset of the error detectors and a subset of the cleansers.

Automatic correction of intensity nonuniformity from sparseness of gradient distribution in medical images.

PubMed

Zheng, Yuanjie; Grossman, Murray; Awate, Suyash P; Gee, James C

2009-01-01

We propose to use the sparseness property of the gradient probability distribution to estimate the intensity nonuniformity in medical images, resulting in two novel automatic methods: a non-parametric method and a parametric method. Our methods are easy to implement because they both solve an iteratively re-weighted least squares problem. They are remarkably accurate as shown by our experiments on images of different imaged objects and from different imaging modalities.

Automatic Correction of Intensity Nonuniformity from Sparseness of Gradient Distribution in Medical Images

PubMed Central

Zheng, Yuanjie; Grossman, Murray; Awate, Suyash P.; Gee, James C.

2013-01-01

We propose to use the sparseness property of the gradient probability distribution to estimate the intensity nonuniformity in medical images, resulting in two novel automatic methods: a non-parametric method and a parametric method. Our methods are easy to implement because they both solve an iteratively re-weighted least squares problem. They are remarkably accurate as shown by our experiments on images of different imaged objects and from different imaging modalities. PMID:20426191

Multiple layer identification label using stacked identification symbols

NASA Technical Reports Server (NTRS)

Schramm, Harry F. (Inventor)

2005-01-01

An automatic identification system and method are provided which employ a machine readable multiple layer label. The label has a plurality of machine readable marking layers stacked one upon another. Each of the marking layers encodes an identification symbol detectable using one or more sensing technologies. The various marking layers may comprise the same marking material or each marking layer may comprise a different medium having characteristics detectable by a different sensing technology. These sensing technologies include x-ray, radar, capacitance, thermal, magnetic and ultrasonic. A complete symbol may be encoded within each marking layer or a symbol may be segmented into fragments which are then divided within a single marking layer or encoded across multiple marking layers.

Intelligent condition monitoring method for bearing faults from highly compressed measurements using sparse over-complete features

NASA Astrophysics Data System (ADS)

Ahmed, H. O. A.; Wong, M. L. D.; Nandi, A. K.

2018-01-01

Condition classification of rolling element bearings in rotating machines is important to prevent the breakdown of industrial machinery. A considerable amount of literature has been published on bearing faults classification. These studies aim to determine automatically the current status of a roller element bearing. Of these studies, methods based on compressed sensing (CS) have received some attention recently due to their ability to allow one to sample below the Nyquist sampling rate. This technology has many possible uses in machine condition monitoring and has been investigated as a possible approach for fault detection and classification in the compressed domain, i.e., without reconstructing the original signal. However, previous CS based methods have been found to be too weak for highly compressed data. The present paper explores computationally, for the first time, the effects of sparse autoencoder based over-complete sparse representations on the classification performance of highly compressed measurements of bearing vibration signals. For this study, the CS method was used to produce highly compressed measurements of the original bearing dataset. Then, an effective deep neural network (DNN) with unsupervised feature learning algorithm based on sparse autoencoder is used for learning over-complete sparse representations of these compressed datasets. Finally, the fault classification is achieved using two stages, namely, pre-training classification based on stacked autoencoder and softmax regression layer form the deep net stage (the first stage), and re-training classification based on backpropagation (BP) algorithm forms the fine-tuning stage (the second stage). The experimental results show that the proposed method is able to achieve high levels of accuracy even with extremely compressed measurements compared with the existing techniques.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pasquier, David; Lacornerie, Thomas; Vermandel, Maximilien

Purpose: Target-volume and organ-at-risk delineation is a time-consuming task in radiotherapy planning. The development of automated segmentation tools remains problematic, because of pelvic organ shape variability. We evaluate a three-dimensional (3D), deformable-model approach and a seeded region-growing algorithm for automatic delineation of the prostate and organs-at-risk on magnetic resonance images. Methods and Materials: Manual and automatic delineation were compared in 24 patients using a sagittal T2-weighted (T2-w) turbo spin echo (TSE) sequence and an axial T1-weighted (T1-w) 3D fast-field echo (FFE) or TSE sequence. For automatic prostate delineation, an organ model-based method was used. Prostates without seminal vesicles were delineatedmore » as the clinical target volume (CTV). For automatic bladder and rectum delineation, a seeded region-growing method was used. Manual contouring was considered the reference method. The following parameters were measured: volume ratio (Vr) (automatic/manual), volume overlap (Vo) (ratio of the volume of intersection to the volume of union; optimal value = 1), and correctly delineated volume (Vc) (percent ratio of the volume of intersection to the manually defined volume; optimal value 100). Results: For the CTV, the Vr, Vo, and Vc were 1.13 ({+-}0.1 SD), 0.78 ({+-}0.05 SD), and 94.75 ({+-}3.3 SD), respectively. For the rectum, the Vr, Vo, and Vc were 0.97 ({+-}0.1 SD), 0.78 ({+-}0.06 SD), and 86.52 ({+-}5 SD), respectively. For the bladder, the Vr, Vo, and Vc were 0.95 ({+-}0.03 SD), 0.88 ({+-}0.03 SD), and 91.29 ({+-}3.1 SD), respectively. Conclusions: Our results show that the organ-model method is robust, and results in reproducible prostate segmentation with minor interactive corrections. For automatic bladder and rectum delineation, magnetic resonance imaging soft-tissue contrast enables the use of region-growing methods.« less

Segmentation of stereo terrain images

NASA Astrophysics Data System (ADS)

George, Debra A.; Privitera, Claudio M.; Blackmon, Theodore T.; Zbinden, Eric; Stark, Lawrence W.

2000-06-01

We have studied four approaches to segmentation of images: three automatic ones using image processing algorithms and a fourth approach, human manual segmentation. We were motivated toward helping with an important NASA Mars rover mission task -- replacing laborious manual path planning with automatic navigation of the rover on the Mars terrain. The goal of the automatic segmentations was to identify an obstacle map on the Mars terrain to enable automatic path planning for the rover. The automatic segmentation was first explored with two different segmentation methods: one based on pixel luminance, and the other based on pixel altitude generated through stereo image processing. The third automatic segmentation was achieved by combining these two types of image segmentation. Human manual segmentation of Martian terrain images was used for evaluating the effectiveness of the combined automatic segmentation as well as for determining how different humans segment the same images. Comparisons between two different segmentations, manual or automatic, were measured using a similarity metric, SAB. Based on this metric, the combined automatic segmentation did fairly well in agreeing with the manual segmentation. This was a demonstration of a positive step towards automatically creating the accurate obstacle maps necessary for automatic path planning and rover navigation.

Automatic Clustering Using FSDE-Forced Strategy Differential Evolution

NASA Astrophysics Data System (ADS)

Yasid, A.

2018-01-01

Clustering analysis is important in datamining for unsupervised data, cause no adequate prior knowledge. One of the important tasks is defining the number of clusters without user involvement that is known as automatic clustering. This study intends on acquiring cluster number automatically utilizing forced strategy differential evolution (AC-FSDE). Two mutation parameters, namely: constant parameter and variable parameter are employed to boost differential evolution performance. Four well-known benchmark datasets were used to evaluate the algorithm. Moreover, the result is compared with other state of the art automatic clustering methods. The experiment results evidence that AC-FSDE is better or competitive with other existing automatic clustering algorithm.

Chemometric strategy for automatic chromatographic peak detection and background drift correction in chromatographic data.

PubMed

Yu, Yong-Jie; Xia, Qiao-Ling; Wang, Sheng; Wang, Bing; Xie, Fu-Wei; Zhang, Xiao-Bing; Ma, Yun-Ming; Wu, Hai-Long

2014-09-12

Peak detection and background drift correction (BDC) are the key stages in using chemometric methods to analyze chromatographic fingerprints of complex samples. This study developed a novel chemometric strategy for simultaneous automatic chromatographic peak detection and BDC. A robust statistical method was used for intelligent estimation of instrumental noise level coupled with first-order derivative of chromatographic signal to automatically extract chromatographic peaks in the data. A local curve-fitting strategy was then employed for BDC. Simulated and real liquid chromatographic data were designed with various kinds of background drift and degree of overlapped chromatographic peaks to verify the performance of the proposed strategy. The underlying chromatographic peaks can be automatically detected and reasonably integrated by this strategy. Meanwhile, chromatograms with BDC can be precisely obtained. The proposed method was used to analyze a complex gas chromatography dataset that monitored quality changes in plant extracts during storage procedure. Copyright © 2014 Elsevier B.V. All rights reserved.

Automatic detection of cardiac cycle and measurement of the mitral annulus diameter in 4D TEE images

NASA Astrophysics Data System (ADS)

Graser, Bastian; Hien, Maximilian; Rauch, Helmut; Meinzer, Hans-Peter; Heimann, Tobias

2012-02-01

Mitral regurgitation is a wide spread problem. For successful surgical treatment quantification of the mitral annulus, especially its diameter, is essential. Time resolved 3D transesophageal echocardiography (TEE) is suitable for this task. Yet, manual measurement in four dimensions is extremely time consuming, which confirms the need for automatic quantification methods. The method we propose is capable of automatically detecting the cardiac cycle (systole or diastole) for each time step and measuring the mitral annulus diameter. This is done using total variation noise filtering, the graph cut segmentation algorithm and morphological operators. An evaluation took place using expert measurements on 4D TEE data of 13 patients. The cardiac cycle was detected correctly on 78% of all images and the mitral annulus diameter was measured with an average error of 3.08 mm. Its full automatic processing makes the method easy to use in the clinical workflow and it provides the surgeon with helpful information.

A hybrid 3D region growing and 4D curvature analysis-based automatic abdominal blood vessel segmentation through contrast enhanced CT

NASA Astrophysics Data System (ADS)

Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Shimada, Mitsuo; Iinuma, Gen

2017-03-01

In abdominal disease diagnosis and various abdominal surgeries planning, segmentation of abdominal blood vessel (ABVs) is a very imperative task. Automatic segmentation enables fast and accurate processing of ABVs. We proposed a fully automatic approach for segmenting ABVs through contrast enhanced CT images by a hybrid of 3D region growing and 4D curvature analysis. The proposed method comprises three stages. First, candidates of bone, kidneys, ABVs and heart are segmented by an auto-adapted threshold. Second, bone is auto-segmented and classified into spine, ribs and pelvis. Third, ABVs are automatically segmented in two sub-steps: (1) kidneys and abdominal part of the heart are segmented, (2) ABVs are segmented by a hybrid approach that integrates a 3D region growing and 4D curvature analysis. Results are compared with two conventional methods. Results show that the proposed method is very promising in segmenting and classifying bone, segmenting whole ABVs and may have potential utility in clinical use.

GIS Data Based Automatic High-Fidelity 3D Road Network Modeling

NASA Technical Reports Server (NTRS)

Wang, Jie; Shen, Yuzhong

2011-01-01

3D road models are widely used in many computer applications such as racing games and driving simulations_ However, almost all high-fidelity 3D road models were generated manually by professional artists at the expense of intensive labor. There are very few existing methods for automatically generating 3D high-fidelity road networks, especially those existing in the real world. This paper presents a novel approach thai can automatically produce 3D high-fidelity road network models from real 2D road GIS data that mainly contain road. centerline in formation. The proposed method first builds parametric representations of the road centerlines through segmentation and fitting . A basic set of civil engineering rules (e.g., cross slope, superelevation, grade) for road design are then selected in order to generate realistic road surfaces in compliance with these rules. While the proposed method applies to any types of roads, this paper mainly addresses automatic generation of complex traffic interchanges and intersections which are the most sophisticated elements in the road networks

Cerebral Correlates of Automatic Associations Towards Performance Enhancing Substances

PubMed Central

Schindler, Sebastian; Wolff, Wanja

2015-01-01

The direct assessment of explicit attitudes toward performance enhancing substances, for example Neuroenhancement or doping in sports, can be affected by social desirability biases and cheating attempts. According to Dual Process Theories of cognition, indirect measures like the Implicit Association Test (IAT) measure automatic associations toward a topic (as opposed to explicit attitudes measured by self-report measures). Such automatic associations are thought to occur rapidly and to evade voluntary control. However, whether or not such indirect tests actually reflect automatic associations is difficult to validate. Electroencephalography (EEG) has a superior time resolution which can differentiate between highly automatic compared to more elaborate processing stages. We therefore used EEG to examine on which processing stages cortical differences between negative or positive attitudes to doping occur, and whether or not these differences can be related to BIAT scores. We tested 42 university students (31 females, 24.43 ± 3.17 years old), who were requested to complete a brief doping IAT (BIAT) on attitudes toward doping. Cerebral activity during doping BIAT completion was assessed using high-density EEG. Behaviorally, participants D-scores exhibited negative attitudes toward doping, represented by faster reaction times in the doping + dislike pairing task. Event-related potentials (ERPs) revealed earliest effects between 200 and 300 ms. Here, a relatively larger occipital positivity was found for the doping + dislike pairing task. Further, in the LPP time range between 400 and 600 ms a larger late positive potential was found for the doping + dislike pairing task over central regions. These LPP amplitude differences were successfully predicting participants' BIAT D-scores. Results indicate that event-related potentials differentiate between positive and negative doping attitudes at stages of mid-latency. However, it seems that IAT scores can be predicted only by the later occurring LPP. Our study is the first to investigate the cerebral correlates that contribute to test scores obtained in the indirect testing of automatic associations toward doping. The implications of our results for the broader NE concept are discussed in light of the conceptual similarity of doping and NE. PMID:26733914

Terminologies for text-mining; an experiment in the lipoprotein metabolism domain

PubMed Central

Alexopoulou, Dimitra; Wächter, Thomas; Pickersgill, Laura; Eyre, Cecilia; Schroeder, Michael

2008-01-01

Background The engineering of ontologies, especially with a view to a text-mining use, is still a new research field. There does not yet exist a well-defined theory and technology for ontology construction. Many of the ontology design steps remain manual and are based on personal experience and intuition. However, there exist a few efforts on automatic construction of ontologies in the form of extracted lists of terms and relations between them. Results We share experience acquired during the manual development of a lipoprotein metabolism ontology (LMO) to be used for text-mining. We compare the manually created ontology terms with the automatically derived terminology from four different automatic term recognition (ATR) methods. The top 50 predicted terms contain up to 89% relevant terms. For the top 1000 terms the best method still generates 51% relevant terms. In a corpus of 3066 documents 53% of LMO terms are contained and 38% can be generated with one of the methods. Conclusions Given high precision, automatic methods can help decrease development time and provide significant support for the identification of domain-specific vocabulary. The coverage of the domain vocabulary depends strongly on the underlying documents. Ontology development for text mining should be performed in a semi-automatic way; taking ATR results as input and following the guidelines we described. Availability The TFIDF term recognition is available as Web Service, described at PMID:18460175

Target recognition based on convolutional neural network

NASA Astrophysics Data System (ADS)

Wang, Liqiang; Wang, Xin; Xi, Fubiao; Dong, Jian

2017-11-01

One of the important part of object target recognition is the feature extraction, which can be classified into feature extraction and automatic feature extraction. The traditional neural network is one of the automatic feature extraction methods, while it causes high possibility of over-fitting due to the global connection. The deep learning algorithm used in this paper is a hierarchical automatic feature extraction method, trained with the layer-by-layer convolutional neural network (CNN), which can extract the features from lower layers to higher layers. The features are more discriminative and it is beneficial to the object target recognition.

Automated feature detection and identification in digital point-ordered signals

DOEpatents

Oppenlander, Jane E.; Loomis, Kent C.; Brudnoy, David M.; Levy, Arthur J.

1998-01-01

A computer-based automated method to detect and identify features in digital point-ordered signals. The method is used for processing of non-destructive test signals, such as eddy current signals obtained from calibration standards. The signals are first automatically processed to remove noise and to determine a baseline. Next, features are detected in the signals using mathematical morphology filters. Finally, verification of the features is made using an expert system of pattern recognition methods and geometric criteria. The method has the advantage that standard features can be, located without prior knowledge of the number or sequence of the features. Further advantages are that standard features can be differentiated from irrelevant signal features such as noise, and detected features are automatically verified by parameters extracted from the signals. The method proceeds fully automatically without initial operator set-up and without subjective operator feature judgement.

Diagnostic support for glaucoma using retinal images: a hybrid image analysis and data mining approach.

PubMed

Yu, Jin; Abidi, Syed Sibte Raza; Artes, Paul; McIntyre, Andy; Heywood, Malcolm

2005-01-01

The availability of modern imaging techniques such as Confocal Scanning Laser Tomography (CSLT) for capturing high-quality optic nerve images offer the potential for developing automatic and objective methods for diagnosing glaucoma. We present a hybrid approach that features the analysis of CSLT images using moment methods to derive abstract image defining features. The features are then used to train classifers for automatically distinguishing CSLT images of normal and glaucoma patient. As a first, in this paper, we present investigations in feature subset selction methods for reducing the relatively large input space produced by the moment methods. We use neural networks and support vector machines to determine a sub-set of moments that offer high classification accuracy. We demonstratee the efficacy of our methods to discriminate between healthy and glaucomatous optic disks based on shape information automatically derived from optic disk topography and reflectance images.

An automatic rat brain extraction method based on a deformable surface model.

PubMed

Li, Jiehua; Liu, Xiaofeng; Zhuo, Jiachen; Gullapalli, Rao P; Zara, Jason M

2013-08-15

The extraction of the brain from the skull in medical images is a necessary first step before image registration or segmentation. While pre-clinical MR imaging studies on small animals, such as rats, are increasing, fully automatic imaging processing techniques specific to small animal studies remain lacking. In this paper, we present an automatic rat brain extraction method, the Rat Brain Deformable model method (RBD), which adapts the popular human brain extraction tool (BET) through the incorporation of information on the brain geometry and MR image characteristics of the rat brain. The robustness of the method was demonstrated on T2-weighted MR images of 64 rats and compared with other brain extraction methods (BET, PCNN, PCNN-3D). The results demonstrate that RBD reliably extracts the rat brain with high accuracy (>92% volume overlap) and is robust against signal inhomogeneity in the images. Copyright © 2013 Elsevier B.V. All rights reserved.

Self-contained miniature electronics transceiver provides voice communication in hazardous environment

NASA Technical Reports Server (NTRS)

Cribb, H. E.

1970-01-01

Two-way wireless voice communications system is automatic, provides freedom of movement, allows for complete awareness of the environment, and does not present any additional hazards such as activation of electromagnetic sensitive devices.

Research in Parallel Algorithms and Software for Computational Aerosciences

DOT National Transportation Integrated Search

1996-04-01

Phase I is complete for the development of a Computational Fluid Dynamics : with automatic grid generation and adaptation for the Euler : analysis of flow over complex geometries. SPLITFLOW, an unstructured Cartesian : grid code developed at Lockheed...

[A computer tomography assisted method for the automatic detection of region of interest in dynamic kidney images].

PubMed

Jing, Xueping; Zheng, Xiujuan; Song, Shaoli; Liu, Kai

2017-12-01

Glomerular filtration rate (GFR), which can be estimated by Gates method with dynamic kidney single photon emission computed tomography (SPECT) imaging, is a key indicator of renal function. In this paper, an automatic computer tomography (CT)-assisted detection method of kidney region of interest (ROI) is proposed to achieve the objective and accurate GFR calculation. In this method, the CT coronal projection image and the enhanced SPECT synthetic image are firstly generated and registered together. Then, the kidney ROIs are delineated using a modified level set algorithm. Meanwhile, the background ROIs are also obtained based on the kidney ROIs. Finally, the value of GFR is calculated via Gates method. Comparing with the clinical data, the GFR values estimated by the proposed method were consistent with the clinical reports. This automatic method can improve the accuracy and stability of kidney ROI detection for GFR calculation, especially when the kidney function has been severely damaged.

Commercially Available Digital Game Technology in the Classroom: Improving Automaticity in Mental-Maths in Primary-Aged Students

ERIC Educational Resources Information Center

O'Rourke, John; Main, Susan; Hill, Susan M.

2017-01-01

In this paper we report on a study of the implementation of handheld game consoles (HGCs) in 10 Year four/five classrooms to develop student automaticity of mathematical calculations. The automaticity of mathematical calculations was compared for those students using the HGC and those being taught using traditional teaching methods. Over a school…

Automatic segmentation of the left ventricle in a cardiac MR short axis image using blind morphological operation

NASA Astrophysics Data System (ADS)

Irshad, Mehreen; Muhammad, Nazeer; Sharif, Muhammad; Yasmeen, Mussarat

2018-04-01

Conventionally, cardiac MR image analysis is done manually. Automatic examination for analyzing images can replace the monotonous tasks of massive amounts of data to analyze the global and regional functions of the cardiac left ventricle (LV). This task is performed using MR images to calculate the analytic cardiac parameter like end-systolic volume, end-diastolic volume, ejection fraction, and myocardial mass, respectively. These analytic parameters depend upon genuine delineation of epicardial, endocardial, papillary muscle, and trabeculations contours. In this paper, we propose an automatic segmentation method using the sum of absolute differences technique to localize the left ventricle. Blind morphological operations are proposed to segment and detect the LV contours of the epicardium and endocardium, automatically. We test the benchmark Sunny Brook dataset for evaluation of the proposed work. Contours of epicardium and endocardium are compared quantitatively to determine contour's accuracy and observe high matching values. Similarity or overlapping of an automatic examination to the given ground truth analysis by an expert are observed with high accuracy as with an index value of 91.30% . The proposed method for automatic segmentation gives better performance relative to existing techniques in terms of accuracy.

Application of software technology to automatic test data analysis

NASA Technical Reports Server (NTRS)

Stagner, J. R.

1991-01-01

The verification process for a major software subsystem was partially automated as part of a feasibility demonstration. The methods employed are generally useful and applicable to other types of subsystems. The effort resulted in substantial savings in test engineer analysis time and offers a method for inclusion of automatic verification as a part of regression testing.

Study of Adaptive Mathematical Models for Deriving Automated Pilot Performance Measurement Techniques. Volume I. Model Development.

ERIC Educational Resources Information Center

Connelly, Edward A.; And Others

A new approach to deriving human performance measures and criteria for use in automatically evaluating trainee performance is documented in this report. The ultimate application of the research is to provide methods for automatically measuring pilot performance in a flight simulator or from recorded in-flight data. An efficient method of…

Automatic Method of Pause Measurement for Normal and Dysarthric Speech

ERIC Educational Resources Information Center

Rosen, Kristin; Murdoch, Bruce; Folker, Joanne; Vogel, Adam; Cahill, Louise; Delatycki, Martin; Corben, Louise

2010-01-01

This study proposes an automatic method for the detection of pauses and identification of pause types in conversational speech for the purpose of measuring the effects of Friedreich's Ataxia (FRDA) on speech. Speech samples of [approximately] 3 minutes were recorded from 13 speakers with FRDA and 18 healthy controls. Pauses were measured from the…

Automatic brain caudate nuclei segmentation and classification in diagnostic of Attention-Deficit/Hyperactivity Disorder.

PubMed

Igual, Laura; Soliva, Joan Carles; Escalera, Sergio; Gimeno, Roger; Vilarroya, Oscar; Radeva, Petia

2012-12-01

We present a fully automatic diagnostic imaging test for Attention-Deficit/Hyperactivity Disorder diagnosis assistance based on previously found evidences of caudate nucleus volumetric abnormalities. The proposed method consists of different steps: a new automatic method for external and internal segmentation of caudate based on Machine Learning methodologies; the definition of a set of new volume relation features, 3D Dissociated Dipoles, used for caudate representation and classification. We separately validate the contributions using real data from a pediatric population and show precise internal caudate segmentation and discrimination power of the diagnostic test, showing significant performance improvements in comparison to other state-of-the-art methods. Copyright © 2012 Elsevier Ltd. All rights reserved.

A new artefacts resistant method for automatic lineament extraction using Multi-Hillshade Hierarchic Clustering (MHHC)

NASA Astrophysics Data System (ADS)

Šilhavý, Jakub; Minár, Jozef; Mentlík, Pavel; Sládek, Ján

2016-07-01

This paper presents a new method of automatic lineament extraction which includes the removal of the 'artefacts effect' which is associated with the process of raster based analysis. The core of the proposed Multi-Hillshade Hierarchic Clustering (MHHC) method incorporates a set of variously illuminated and rotated hillshades in combination with hierarchic clustering of derived 'protolineaments'. The algorithm also includes classification into positive and negative lineaments. MHHC was tested in two different territories in Bohemian Forest and Central Western Carpathians. The original vector-based algorithm was developed for comparison of the individual lineaments proximity. Its use confirms the compatibility of manual and automatic extraction and their similar relationships to structural data in the study areas.

First- and Second-Order Sensitivity Analysis of a P-Version Finite Element Equation Via Automatic Differentiation

NASA Technical Reports Server (NTRS)

Hou, Gene

1998-01-01

Sensitivity analysis is a technique for determining derivatives of system responses with respect to design parameters. Among many methods available for sensitivity analysis, automatic differentiation has been proven through many applications in fluid dynamics and structural mechanics to be an accurate and easy method for obtaining derivatives. Nevertheless, the method can be computational expensive and can require a high memory space. This project will apply an automatic differentiation tool, ADIFOR, to a p-version finite element code to obtain first- and second- order then-nal derivatives, respectively. The focus of the study is on the implementation process and the performance of the ADIFOR-enhanced codes for sensitivity analysis in terms of memory requirement, computational efficiency, and accuracy.

Annotation-based inference of transporter function.

PubMed

Lee, Thomas J; Paulsen, Ian; Karp, Peter

2008-07-01

We present a method for inferring and constructing transport reactions for transporter proteins based primarily on the analysis of the names of individual proteins in the genome annotation of an organism. Transport reactions are declarative descriptions of transporter activities, and thus can be manipulated computationally, unlike free-text protein names. Once transporter activities are encoded as transport reactions, a number of computational analyses are possible including database queries by transporter activity; inclusion of transporters into an automatically generated metabolic-map diagram that can be painted with omics data to aid in their interpretation; detection of anomalies in the metabolic and transport networks, such as substrates that are transported into the cell but are not inputs to any metabolic reaction or pathway; and comparative analyses of the transport capabilities of different organisms. On randomly selected organisms, the method achieves precision and recall rates of 0.93 and 0.90, respectively in identifying transporter proteins by name within the complete genome. The method obtains 67.5% accuracy in predicting complete transport reactions; if allowance is made for predictions that are overly general yet not incorrect, reaction prediction accuracy is 82.5%. The method is implemented as part of PathoLogic, the inference component of the Pathway Tools software. Pathway Tools is freely available to researchers at non-commercial institutions, including source code; a fee applies to commercial institutions. Supplementary data are available at Bioinformatics online.

Integrating long-offset transient electromagnetics (LOTEM) with seismics in an exploration environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Strack, K.M.; Vozoff, K.

The applications of electromagnetics have increased in the past two decades because of an improved understanding of the methods, improves service availability, and the increased focus of exploration in the more complex reservoir characterization issues. For electromagnetic methods surface applications for hydrocarbon Exploration and Production are still a special case, while applications in borehole and airborne research and for engineering and environmental objectives are routine. In the past, electromagnetic techniques, in particular deep transient electromagnetics, made up a completely different discipline in geophysics, although many of the principles are similar to the seismic one. With an understanding of the specificmore » problems related to data processing initially and then acquisition, the inclusion of principles learned from seismics happened almost naturally. Initially, the data processing was very similar to seismic full-waveform processing. The hardware was also changed to include multichannel acquisition systems, and the field procedures became very similar to seismic surveying. As a consequence, the integration and synergism of the interpretation process is becoming almost automatic. The long-offset transient electromagnetic (LOTEM) technique will be summarized from the viewpoint of its similarity to seismics. The complete concept of the method will also be reviewed. An interpretation case history that integrates seismic and LOTEM from a hydrocarbon area in China clearly demonstrates the limitations and benefits of the method.« less

Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Baochun; Huang, Cheng; Zhou, Shoujun

Purpose: A robust, automatic, and rapid method for liver delineation is urgently needed for the diagnosis and treatment of liver disorders. Until now, the high variability in liver shape, local image artifacts, and the presence of tumors have complicated the development of automatic 3D liver segmentation. In this study, an automatic three-level AdaBoost-guided active shape model (ASM) is proposed for the segmentation of the liver based on enhanced computed tomography images in a robust and fast manner, with an emphasis on the detection of tumors. Methods: The AdaBoost voxel classifier and AdaBoost profile classifier were used to automatically guide three-levelmore » active shape modeling. In the first level of model initialization, fast automatic liver segmentation by an AdaBoost voxel classifier method is proposed. A shape model is then initialized by registration with the resulting rough segmentation. In the second level of active shape model fitting, a prior model based on the two-class AdaBoost profile classifier is proposed to identify the optimal surface. In the third level, a deformable simplex mesh with profile probability and curvature constraint as the external force is used to refine the shape fitting result. In total, three registration methods—3D similarity registration, probability atlas B-spline, and their proposed deformable closest point registration—are used to establish shape correspondence. Results: The proposed method was evaluated using three public challenge datasets: 3Dircadb1, SLIVER07, and Visceral Anatomy3. The results showed that our approach performs with promising efficiency, with an average of 35 s, and accuracy, with an average Dice similarity coefficient (DSC) of 0.94 ± 0.02, 0.96 ± 0.01, and 0.94 ± 0.02 for the 3Dircadb1, SLIVER07, and Anatomy3 training datasets, respectively. The DSC of the SLIVER07 testing and Anatomy3 unseen testing datasets were 0.964 and 0.933, respectively. Conclusions: The proposed automatic approach achieves robust, accurate, and fast liver segmentation for 3D CTce datasets. The AdaBoost voxel classifier can detect liver area quickly without errors and provides sufficient liver shape information for model initialization. The AdaBoost profile classifier achieves sufficient accuracy and greatly decreases segmentation time. These results show that the proposed segmentation method achieves a level of accuracy comparable to that of state-of-the-art automatic methods based on ASM.« less

Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model.

PubMed

He, Baochun; Huang, Cheng; Sharp, Gregory; Zhou, Shoujun; Hu, Qingmao; Fang, Chihua; Fan, Yingfang; Jia, Fucang

2016-05-01

A robust, automatic, and rapid method for liver delineation is urgently needed for the diagnosis and treatment of liver disorders. Until now, the high variability in liver shape, local image artifacts, and the presence of tumors have complicated the development of automatic 3D liver segmentation. In this study, an automatic three-level AdaBoost-guided active shape model (ASM) is proposed for the segmentation of the liver based on enhanced computed tomography images in a robust and fast manner, with an emphasis on the detection of tumors. The AdaBoost voxel classifier and AdaBoost profile classifier were used to automatically guide three-level active shape modeling. In the first level of model initialization, fast automatic liver segmentation by an AdaBoost voxel classifier method is proposed. A shape model is then initialized by registration with the resulting rough segmentation. In the second level of active shape model fitting, a prior model based on the two-class AdaBoost profile classifier is proposed to identify the optimal surface. In the third level, a deformable simplex mesh with profile probability and curvature constraint as the external force is used to refine the shape fitting result. In total, three registration methods-3D similarity registration, probability atlas B-spline, and their proposed deformable closest point registration-are used to establish shape correspondence. The proposed method was evaluated using three public challenge datasets: 3Dircadb1, SLIVER07, and Visceral Anatomy3. The results showed that our approach performs with promising efficiency, with an average of 35 s, and accuracy, with an average Dice similarity coefficient (DSC) of 0.94 ± 0.02, 0.96 ± 0.01, and 0.94 ± 0.02 for the 3Dircadb1, SLIVER07, and Anatomy3 training datasets, respectively. The DSC of the SLIVER07 testing and Anatomy3 unseen testing datasets were 0.964 and 0.933, respectively. The proposed automatic approach achieves robust, accurate, and fast liver segmentation for 3D CTce datasets. The AdaBoost voxel classifier can detect liver area quickly without errors and provides sufficient liver shape information for model initialization. The AdaBoost profile classifier achieves sufficient accuracy and greatly decreases segmentation time. These results show that the proposed segmentation method achieves a level of accuracy comparable to that of state-of-the-art automatic methods based on ASM.

Method and system for spatial data input, manipulation and distribution via an adaptive wireless transceiver

NASA Technical Reports Server (NTRS)

Wang, Ray (Inventor)

2009-01-01

A method and system for spatial data manipulation input and distribution via an adaptive wireless transceiver. The method and system include a wireless transceiver for automatically and adaptively controlling wireless transmissions using a Waveform-DNA method. The wireless transceiver can operate simultaneously over both the short and long distances. The wireless transceiver is automatically adaptive and wireless devices can send and receive wireless digital and analog data from various sources rapidly in real-time via available networks and network services.

Attentional Bias for Pain and Sex, and Automatic Appraisals of Sexual Penetration: Differential Patterns in Dyspareunia vs Vaginismus?

PubMed

Melles, Reinhilde J; Dewitte, Marieke D; Ter Kuile, Moniek M; Peters, Madelon M L; de Jong, Peter J

2016-08-01

Current information processing models propose that heightened attention bias for sex-related threats (eg, pain) and lowered automatic incentive processes ("wanting") may play an important role in the impairment of sexual arousal and the development of sexual dysfunctions such as genitopelvic pain/penetration disorder (GPPPD). Differential threat and incentive processing may also help explain the stronger persistence of coital avoidance in women with vaginismus compared to women with dyspareunia. As the first aim, we tested if women with GPPPD show (1) heightened attention for pain and sex, and (2) heightened threat and lower incentive associations with sexual penetration. Second, we examined whether the stronger persistence of coital avoidance in vaginismus vs dyspareunia might be explained by a stronger attentional bias or more dysfunctional automatic threat/incentive associations. Women with lifelong vaginismus (n = 37), dyspareunia (n = 29), and a no-symptoms comparison group (n = 51) completed a visual search task to assess attentional bias, and single target implicit-association tests to measure automatic sex-threat and sex-wanting associations. There were no group differences in attentional bias or automatic associations. Correlational analysis showed that slowed detection of sex stimuli and stronger automatic threat associations were related to lowered sexual arousal. The findings do not corroborate the view that attentional bias for pain or sex contributes to coital pain, or that differences in coital avoidance may be explained by differences in attentional bias or automatic threat/incentive associations. However, the correlational findings are consistent with the view that automatic threat associations and impaired attention for sex stimuli may interfere with the generation of sexual arousal. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Evaluation of an automatic MR-based gold fiducial marker localisation method for MR-only prostate radiotherapy

NASA Astrophysics Data System (ADS)

Maspero, Matteo; van den Berg, Cornelis A. T.; Zijlstra, Frank; Sikkes, Gonda G.; de Boer, Hans C. J.; Meijer, Gert J.; Kerkmeijer, Linda G. W.; Viergever, Max A.; Lagendijk, Jan J. W.; Seevinck, Peter R.

2017-10-01

An MR-only radiotherapy planning (RTP) workflow would reduce the cost, radiation exposure and uncertainties introduced by CT-MRI registrations. In the case of prostate treatment, one of the remaining challenges currently holding back the implementation of an RTP workflow is the MR-based localisation of intraprostatic gold fiducial markers (FMs), which is crucial for accurate patient positioning. Currently, MR-based FM localisation is clinically performed manually. This is sub-optimal, as manual interaction increases the workload. Attempts to perform automatic FM detection often rely on being able to detect signal voids induced by the FMs in magnitude images. However, signal voids may not always be sufficiently specific, hampering accurate and robust automatic FM localisation. Here, we present an approach that aims at automatic MR-based FM localisation. This method is based on template matching using a library of simulated complex-valued templates, and exploiting the behaviour of the complex MR signal in the vicinity of the FM. Clinical evaluation was performed on seventeen prostate cancer patients undergoing external beam radiotherapy treatment. Automatic MR-based FM localisation was compared to manual MR-based and semi-automatic CT-based localisation (the current gold standard) in terms of detection rate and the spatial accuracy and precision of localisation. The proposed method correctly detected all three FMs in 15/17 patients. The spatial accuracy (mean) and precision (STD) were 0.9 mm and 0.5 mm respectively, which is below the voxel size of 1.1 × 1.1 × 1.2 mm3 and comparable to MR-based manual localisation. FM localisation failed (3/51 FMs) in the presence of bleeding or calcifications in the direct vicinity of the FM. The method was found to be spatially accurate and precise, which is essential for clinical use. To overcome any missed detection, we envision the use of the proposed method along with verification by an observer. This will result in a semi-automatic workflow facilitating the introduction of an MR-only workflow.

Feasibility of automatic evaluation of clinical rules in general practice.

PubMed

Opondo, Dedan; Visscher, Stefan; Eslami, Saied; Medlock, Stephanie; Verheij, Robert; Korevaar, Joke C; Abu-Hanna, Ameen

2017-04-01

To assess the extent to which clinical rules (CRs) can be implemented for automatic evaluation of quality of care in general practice. We assessed 81 clinical rules (CRs) adapted from a subset of Assessing Care of Vulnerable Elders (ACOVE) clinical rules, against Dutch College of General Practitioners (NHG) data model. Each CR was analyzed using the Logical Elements Rule METHOD: (LERM). LERM is a stepwise method of assessing and formalizing clinical rules for decision support. Clinical rules that satisfied the criteria outlined in the LERM method were judged to be implementable in automatic evaluation in general practice. Thirty-three out of 81 (40.7%) Dutch-translated ACOVE clinical rules can be automatically evaluated in electronic medical record systems. Seven out of 7 CRs (100%) in the domain of diabetes can be automatically evaluated, 9/17 (52.9%) in medication use, 5/10 (50%) in depression care, 3/6 (50%) in nutrition care, 6/13 (46.1%) in dementia care, 1/6 (16.6%) in end of life care, 2/13 (15.3%) in continuity of care, and 0/9 (0%) in the fall-related care. Lack of documentation of care activities between primary and secondary health facilities and ambiguous formulation of clinical rules were the main reasons for the inability to automate the clinical rules. Approximately two-fifths of the primary care Dutch ACOVE-based clinical rules can be automatically evaluated. Clear definition of clinical rules, improved GP database design and electronic linkage of primary and secondary healthcare facilities can improve prospects of automatic assessment of quality of care. These findings are relevant especially because the Netherlands has very high automation of primary care. Copyright © 2017 Elsevier B.V. All rights reserved.

Automatic sleep stage classification using two-channel electro-oculography.

PubMed

Virkkala, Jussi; Hasan, Joel; Värri, Alpo; Himanen, Sari-Leena; Müller, Kiti

2007-10-15

An automatic method for the classification of wakefulness and sleep stages SREM, S1, S2 and SWS was developed based on our two previous studies. The method is based on a two-channel electro-oculography (EOG) referenced to the left mastoid (M1). Synchronous electroencephalographic (EEG) activity in S2 and SWS was detected by calculating cross-correlation and peak-to-peak amplitude difference in the 0.5-6 Hz band between the two EOG channels. An automatic slow eye-movement (SEM) estimation was used to indicate wakefulness, SREM and S1. Beta power 18-30 Hz and alpha power 8-12 Hz was also used for wakefulness detection. Synchronous 1.5-6 Hz EEG activity and absence of large eye movements was used for S1 separation from SREM. Simple smoothing rules were also applied. Sleep EEG, EOG and EMG were recorded from 265 subjects. The system was tuned using data from 132 training subjects and then applied to data from 131 validation subjects that were different to the training subjects. Cohen's Kappa between the visual and the developed new automatic scoring in separating 30s wakefulness, SREM, S1, S2 and SWS epochs was substantial 0.62 with epoch by epoch agreement of 72%. With automatic subject specific alpha thresholds for offline applications results improved to 0.63 and 73%. The automatic method can be further developed and applied for ambulatory sleep recordings by using only four disposable, self-adhesive and self-applicable electrodes.

Evidence that attitude accessibility augments the relationship between speeding attitudes and speeding behavior: a test of the MODE model in the context of driving.

PubMed

Elliott, Mark A; Lee, Emme; Robertson, Jamie S; Innes, Rhona

2015-01-01

According to the MODE model of attitude-to-behavior processes, attitude accessibility augments attitude-behavior correspondence, reflecting an automatic influence of attitudes on behavior. We therefore tested whether attitude accessibility moderates the attitude-behavior relationship in a context that is governed by characteristically automatic behavior, namely driving. In study 1 (correlational design), participants (N=130) completed online questionnaire measures of the valences and accessibilities of their attitudes towards speeding. Two weeks later, online questionnaire measures of subsequent speeding behavior were obtained. Attitude valence was a significantly better predictor of behavior at high (mean+1SD) versus low (mean-1SD) levels of attitude accessibility. In study 2 (experimental design), attitude accessibility was manipulated with a repeated attitude expression task. Immediately after the manipulation, participants (N=122) completed online questionnaire measures of attitude valence and accessibility, and two weeks later, subsequent speeding behavior. Increased attitude accessibility in the experimental (versus control) condition generated an increase in attitude-behavior correspondence. The findings are consistent with the MODE model's proposition that attitudes can exert an automatic influence on behavior. Interventions to reduce speeding could usefully increase the accessibility of anti-speeding attitudes and reduce the accessibility of pro-speeding attitudes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Automatic Extraction of Urban Built-Up Area Based on Object-Oriented Method and Remote Sensing Data

NASA Astrophysics Data System (ADS)

Li, L.; Zhou, H.; Wen, Q.; Chen, T.; Guan, F.; Ren, B.; Yu, H.; Wang, Z.

2018-04-01

Built-up area marks the use of city construction land in the different periods of the development, the accurate extraction is the key to the studies of the changes of urban expansion. This paper studies the technology of automatic extraction of urban built-up area based on object-oriented method and remote sensing data, and realizes the automatic extraction of the main built-up area of the city, which saves the manpower cost greatly. First, the extraction of construction land based on object-oriented method, the main technical steps include: (1) Multi-resolution segmentation; (2) Feature Construction and Selection; (3) Information Extraction of Construction Land Based on Rule Set, The characteristic parameters used in the rule set mainly include the mean of the red band (Mean R), Normalized Difference Vegetation Index (NDVI), Ratio of residential index (RRI), Blue band mean (Mean B), Through the combination of the above characteristic parameters, the construction site information can be extracted. Based on the degree of adaptability, distance and area of the object domain, the urban built-up area can be quickly and accurately defined from the construction land information without depending on other data and expert knowledge to achieve the automatic extraction of the urban built-up area. In this paper, Beijing city as an experimental area for the technical methods of the experiment, the results show that: the city built-up area to achieve automatic extraction, boundary accuracy of 2359.65 m to meet the requirements. The automatic extraction of urban built-up area has strong practicality and can be applied to the monitoring of the change of the main built-up area of city.

Challenges and Opportunities: One Stop Processing of Automatic Large-Scale Base Map Production Using Airborne LIDAR Data Within GIS Environment. Case Study: Makassar City, Indonesia

NASA Astrophysics Data System (ADS)

Widyaningrum, E.; Gorte, B. G. H.

2017-05-01

LiDAR data acquisition is recognized as one of the fastest solutions to provide basis data for large-scale topographical base maps worldwide. Automatic LiDAR processing is believed one possible scheme to accelerate the large-scale topographic base map provision by the Geospatial Information Agency in Indonesia. As a progressive advanced technology, Geographic Information System (GIS) open possibilities to deal with geospatial data automatic processing and analyses. Considering further needs of spatial data sharing and integration, the one stop processing of LiDAR data in a GIS environment is considered a powerful and efficient approach for the base map provision. The quality of the automated topographic base map is assessed and analysed based on its completeness, correctness, quality, and the confusion matrix.

Pilot control through the TAFCOS automatic flight control system

NASA Technical Reports Server (NTRS)

Wehrend, W. R., Jr.

1979-01-01

The set of flight control logic used in a recently completed flight test program to evaluate the total automatic flight control system (TAFCOS) with the controller operating in a fully automatic mode, was used to perform an unmanned simulation on an IBM 360 computer in which the TAFCOS concept was extended to provide a multilevel pilot interface. A pilot TAFCOS interface for direct pilot control by use of a velocity-control-wheel-steering mode was defined as well as a means for calling up conventional autopilot modes. It is concluded that the TAFCOS structure is easily adaptable to the addition of a pilot control through a stick-wheel-throttle control similar to conventional airplane controls. Conventional autopilot modes, such as airspeed-hold, altitude-hold, heading-hold, and flight path angle-hold, can also be included.

General collaboration offer of Johnson Controls regarding the performance of air conditioning automatic control systems and other buildings` automatic control systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gniazdowski, J.

1995-12-31

JOHNSON CONTROLS manufactures measuring and control equipment (800 types) and is as well a {open_quotes}turn-key{close_quotes} supplier of complete automatic controls systems for heating, air conditioning, ventilation and refrigerating engineering branches. The Company also supplies Buildings` Computer-Based Supervision and Monitoring Systems that may be applied in both small and large structures. Since 1990 the company has been performing full-range trade and contracting activities on the Polish market. We have our own well-trained technical staff and we collaborate with a series of designing and contracting enterprises that enable us to have our projects carried out all over Poland. The prices of ourmore » supplies and services correspond with the level of the Polish market.« less

Automatic high-sensitivity control of suspended pollutants in drinking and natural water

NASA Astrophysics Data System (ADS)

Akopov, Edmund I.; Karabegov, M.; Ovanesyan, A.

1993-11-01

This article presents a description of the new instrumental method and device for automatic measurement of water turbidity (WT) by means of photoelectron flow ultramicroscope (PFU). The method presents the WT determination by measuring the number concentration (number of particles suspended in 1 cm3 of water under study) using the PFU and demonstrates much higher sensitivity and accuracy in comparison with the usual methods--turbidimetry and nephelometry.

[An automatic system controlled by microcontroller for carotid sinus perfusion].

PubMed

Yi, X L; Wang, M Y; Fan, Z Z; He, R R

2001-08-01

To establish a new method for controlling automatically the carotid perfusion pressure. A cheap practical automatic perfusion unit based on AT89C2051 micro controller was designed. The unit, LDB-M perfusion pump and the carotid sinus of an animal constituted an automatic perfusion system. This system was able to provide ramp and stepwise updown perfusion pattern and has been used in the research of baroreflex. It can insure the precision and reproducibility of perfusion pressure curve, and improve the technical level in corresponding medical field.

Automatic Residential/Commercial Classification of Parcels with Solar Panel Detections

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morton, April M; Omitaomu, Olufemi A; Kotikot, Susan

A computational method to automatically detect solar panels on rooftops to aid policy and financial assessment of solar distributed generation. The code automatically classifies parcels containing solar panels in the U.S. as residential or commercial. The code allows the user to specify an input dataset containing parcels and detected solar panels, and then uses information about the parcels and solar panels to automatically classify the rooftops as residential or commercial using machine learning techniques. The zip file containing the code includes sample input and output datasets for the Boston and DC areas.

Basic forest cover mapping using digitized remote sensor data and automated data processing techniques

NASA Technical Reports Server (NTRS)

Coggeshall, M. E.; Hoffer, R. M.

1973-01-01

Remote sensing equipment and automatic data processing techniques were employed as aids in the institution of improved forest resource management methods. On the basis of automatically calculated statistics derived from manually selected training samples, the feature selection processor of LARSYS selected, upon consideration of various groups of the four available spectral regions, a series of channel combinations whose automatic classification performances (for six cover types, including both deciduous and coniferous forest) were tested, analyzed, and further compared with automatic classification results obtained from digitized color infrared photography.

A long-term tropical mesoscale convective systems dataset based on a novel objective automatic tracking algorithm

NASA Astrophysics Data System (ADS)

Huang, Xiaomeng; Hu, Chenqi; Huang, Xing; Chu, Yang; Tseng, Yu-heng; Zhang, Guang Jun; Lin, Yanluan

2018-01-01

Mesoscale convective systems (MCSs) are important components of tropical weather systems and the climate system. Long-term data of MCS are of great significance in weather and climate research. Using long-term (1985-2008) global satellite infrared (IR) data, we developed a novel objective automatic tracking algorithm, which combines a Kalman filter (KF) with the conventional area-overlapping method, to generate a comprehensive MCS dataset. The new algorithm can effectively track small and fast-moving MCSs and thus obtain more realistic and complete tracking results than previous studies. A few examples are provided to illustrate the potential application of the dataset with a focus on the diurnal variations of MCSs over land and ocean regions. We find that the MCSs occurring over land tend to initiate in the afternoon with greater intensity, but the oceanic MCSs are more likely to initiate in the early morning with weaker intensity. A double peak in the maximum spatial coverage is noted over the western Pacific, especially over the southwestern Pacific during the austral summer. Oceanic MCSs also persist for approximately 1 h longer than their continental counterparts.

A cost analysis comparing xeroradiography to film technics for intraoral radiography.

PubMed

Gratt, B M; Sickles, E A

1986-01-01

In the United States during 1978 $730 million was spent on dental radiographic services. Currently there are three alternatives for the processing of intraoral radiographs: manual wet-tanks, automatic film units, or xeroradiography. It was the intent of this study to determine which processing system is the most economical. Cost estimates were based on a usage rate of 750 patient images per month and included a calculation of the average cost per radiograph over a five-year period. Capital costs included initial processing equipment and site preparation. Operational costs included labor, supplies, utilities, darkroom rental, and breakdown costs. Clinical time trials were employed to measure examination times. Maintenance logs were employed to assess labor costs. Indirect costs of training were estimated. Results indicated that xeroradiography was the most cost effective ($0.81 per image) compared to either automatic film processing ($1.14 per image) or manual processing ($1.35 per image). Variations in projected costs indicated that if a dental practice performs primarily complete-mouth surveys, exposes less than 120 radiographs per month, and pays less than +6.50 per hour in wages, then manual (wet-tank) processing is the most economical method for producing intraoral radiographs.

From Modelling to Execution of Enterprise Integration Scenarios: The GENIUS Tool

NASA Astrophysics Data System (ADS)

Scheibler, Thorsten; Leymann, Frank

One of the predominant problems IT companies are facing today is Enterprise Application Integration (EAI). Most of the infrastructures built to tackle integration issues are proprietary because no standards exist for how to model, develop, and actually execute integration scenarios. EAI patterns gain importance for non-technical business users to ease and harmonize the development of EAI scenarios. These patterns describe recurring EAI challenges and propose possible solutions in an abstract way. Therefore, one can use those patterns to describe enterprise architectures in a technology neutral manner. However, patterns are documentation only used by developers and systems architects to decide how to implement an integration scenario manually. Thus, patterns are not theoretical thought to stand for artefacts that will immediately be executed. This paper presents a tool supporting a method how EAI patterns can be used to generate executable artefacts for various target platforms automatically using a model-driven development approach, hence turning patterns into something executable. Therefore, we introduce a continuous tool chain beginning at the design phase and ending in executing an integration solution in a completely automatically manner. For evaluation purposes we introduce a scenario demonstrating how the tool is utilized for modelling and actually executing an integration scenario.

Man vs. Machine: An interactive poll to evaluate hydrological model performance of a manual and an automatic calibration

NASA Astrophysics Data System (ADS)

Wesemann, Johannes; Burgholzer, Reinhard; Herrnegger, Mathew; Schulz, Karsten

2017-04-01

In recent years, a lot of research in hydrological modelling has been invested to improve the automatic calibration of rainfall-runoff models. This includes for example (1) the implementation of new optimisation methods, (2) the incorporation of new and different objective criteria and signatures in the optimisation and (3) the usage of auxiliary data sets apart from runoff. Nevertheless, in many applications manual calibration is still justifiable and frequently applied. The hydrologist performing the manual calibration, with his expert knowledge, is able to judge the hydrographs simultaneously concerning details but also in a holistic view. This integrated eye-ball verification procedure available to man can be difficult to formulate in objective criteria, even when using a multi-criteria approach. Comparing the results of automatic and manual calibration is not straightforward. Automatic calibration often solely involves objective criteria such as Nash-Sutcliffe Efficiency Coefficient or the Kling-Gupta-Efficiency as a benchmark during the calibration. Consequently, a comparison based on such measures is intrinsically biased towards automatic calibration. Additionally, objective criteria do not cover all aspects of a hydrograph leaving questions concerning the quality of a simulation open. This contribution therefore seeks to examine the quality of manually and automatically calibrated hydrographs by interactively involving expert knowledge in the evaluation. Simulations have been performed for the Mur catchment in Austria with the rainfall-runoff model COSERO using two parameter sets evolved from a manual and an automatic calibration. A subset of resulting hydrographs for observation and simulation, representing the typical flow conditions and events, will be evaluated in this study. In an interactive crowdsourcing approach experts attending the session can vote for their preferred simulated hydrograph without having information on the calibration method that produced the respective hydrograph. Therefore, the result of the poll can be seen as an additional quality criterion for the comparison of the two different approaches and help in the evaluation of the automatic calibration method.

Automatic labeling of MR brain images through extensible learning and atlas forests.

PubMed

Xu, Lijun; Liu, Hong; Song, Enmin; Yan, Meng; Jin, Renchao; Hung, Chih-Cheng

2017-12-01

Multiatlas-based method is extensively used in MR brain images segmentation because of its simplicity and robustness. This method provides excellent accuracy although it is time consuming and limited in terms of obtaining information about new atlases. In this study, an automatic labeling of MR brain images through extensible learning and atlas forest is presented to address these limitations. We propose an extensible learning model which allows the multiatlas-based framework capable of managing the datasets with numerous atlases or dynamic atlas datasets and simultaneously ensure the accuracy of automatic labeling. Two new strategies are used to reduce the time and space complexity and improve the efficiency of the automatic labeling of brain MR images. First, atlases are encoded to atlas forests through random forest technology to reduce the time consumed for cross-registration between atlases and target image, and a scatter spatial vector is designed to eliminate errors caused by inaccurate registration. Second, an atlas selection method based on the extensible learning model is used to select atlases for target image without traversing the entire dataset and then obtain the accurate labeling. The labeling results of the proposed method were evaluated in three public datasets, namely, IBSR, LONI LPBA40, and ADNI. With the proposed method, the dice coefficient metric values on the three datasets were 84.17 ± 4.61%, 83.25 ± 4.29%, and 81.88 ± 4.53% which were 5% higher than those of the conventional method, respectively. The efficiency of the extensible learning model was evaluated by state-of-the-art methods for labeling of MR brain images. Experimental results showed that the proposed method could achieve accurate labeling for MR brain images without traversing the entire datasets. In the proposed multiatlas-based method, extensible learning and atlas forests were applied to control the automatic labeling of brain anatomies on large atlas datasets or dynamic atlas datasets and obtain accurate results. © 2017 American Association of Physicists in Medicine.

A new method of field MRTD test

NASA Astrophysics Data System (ADS)

Chen, Zhibin; Song, Yan; Liu, Xianhong; Xiao, Wenjian

2014-09-01

MRTD is an important indicator to measure the imaging performance of infrared camera. In the traditional laboratory test, blackbody is used as simulated heat source which is not only expensive and bulky but also difficult to meet field testing requirements of online automatic infrared camera MRTD. To solve this problem, this paper introduces a new detection device for MRTD, which uses LED as a simulation heat source and branded plated zinc sulfide glass carved four-bar target as a simulation target. By using high temperature adaptability cassegrain collimation system, the target is simulated to be distance-infinite so that it can be observed by the human eyes to complete the subjective test, or collected to complete objective measurement by image processing. This method will use LED to replace blackbody. The color temperature of LED is calibrated by thermal imager, thereby, the relation curve between the LED temperature controlling current and the blackbody simulation temperature difference is established, accurately achieved the temperature control of the infrared target. Experimental results show that the accuracy of the device in field testing of thermal imager MRTD can be limited within 0.1K, which greatly reduces the cost to meet the project requirements with a wide application value.

[Gonioscopy - How, Why, What for?

PubMed

Unterlauft, J D

2017-08-01

Aim Gonioscopy is used to exam the anterior chamber angle and the neighbouring structures. Gonioscopy can be performed using a contact lens, with the patient sitting at the slit lamp or in a supine position. Due to the total inner reflection of the cornea, the anterior chamber angle would otherwise be invisible in a healthy eye. During normal daily clinical routine, gonioscopy is often omitted, due to lack of time, although additional information could be gained. Materials and Methods The aim is to give a summary of the diagnostic possibilities using gonioscopy and to emphasise the importance of this relatively easy clinical method. Results The development of gonioscopy, the appropriate tools, proper procedure at the slit lamp and the most popular grading systems are described. In addition, an overview of detectable pathological changes in the anterior chamber angle is given and future prospects about developments in gonioscopy. Conclusion Gonioscopy can provide additional information otherwise missed by slit lamp examination or ophthalmoscopy alone. Up to now, no (semi-)automatic devices have been developed which could completely replace gonioscopy. Therefore gonioscopy remains an important part of a complete ophthalmological examination and should be learned, mastered and performed regularly by every ophthalmologist. Georg Thieme Verlag KG Stuttgart · New York.

Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network.

PubMed

Cui, Shaoguo; Mao, Lei; Jiang, Jingfeng; Liu, Chang; Xiong, Shuyu

2018-01-01

Brain tumors can appear anywhere in the brain and have vastly different sizes and morphology. Additionally, these tumors are often diffused and poorly contrasted. Consequently, the segmentation of brain tumor and intratumor subregions using magnetic resonance imaging (MRI) data with minimal human interventions remains a challenging task. In this paper, we present a novel fully automatic segmentation method from MRI data containing in vivo brain gliomas. This approach can not only localize the entire tumor region but can also accurately segment the intratumor structure. The proposed work was based on a cascaded deep learning convolutional neural network consisting of two subnetworks: (1) a tumor localization network (TLN) and (2) an intratumor classification network (ITCN). The TLN, a fully convolutional network (FCN) in conjunction with the transfer learning technology, was used to first process MRI data. The goal of the first subnetwork was to define the tumor region from an MRI slice. Then, the ITCN was used to label the defined tumor region into multiple subregions. Particularly, ITCN exploited a convolutional neural network (CNN) with deeper architecture and smaller kernel. The proposed approach was validated on multimodal brain tumor segmentation (BRATS 2015) datasets, which contain 220 high-grade glioma (HGG) and 54 low-grade glioma (LGG) cases. Dice similarity coefficient (DSC), positive predictive value (PPV), and sensitivity were used as evaluation metrics. Our experimental results indicated that our method could obtain the promising segmentation results and had a faster segmentation speed. More specifically, the proposed method obtained comparable and overall better DSC values (0.89, 0.77, and 0.80) on the combined (HGG + LGG) testing set, as compared to other methods reported in the literature. Additionally, the proposed approach was able to complete a segmentation task at a rate of 1.54 seconds per slice.

Description of a Remote Ionospheric Scintillation Data Collection Facility

DOT National Transportation Integrated Search

1973-03-01

An experimental technique is described which measures L-band ionospheric scintillation at a remote, unmanned site. Details of an automatic data collection facility are presented. The remote facility comprises an L-band receiver, and a complete VHF co...

a Novel Image Acquisition and Processing Procedure for Fast Tunnel Dsm Production

NASA Astrophysics Data System (ADS)

Roncella, R.; Umili, G.; Forlani, G.

2012-07-01

In mining operations the evaluation of the stability condition of the excavated front are critic to ensure a safe and correct planning of the subsequent activities. The procedure currently used to this aim has some shortcomings: safety for the geologist, completeness of data collection and objective documentation of the results. In the last decade it has been shown that the geostructural parameters necessary to the stability analysis can be derived from high resolution digital surface models (DSM) of rock faces. With the objective to overcome the limitation of the traditional survey and to minimize data capture times, so reducing delays on mining site operations, a photogrammetric system to generate high resolution DSM of tunnels has been realized. A fast, effective and complete data capture method has been developed and the orientation and restitution phases have been largely automated. The survey operations take no more than required to the traditional ones; no additional topographic measurements other than those available are required. To make the data processing fast and economic our Structure from Motion procedure has been slightly modified to adapt to the peculiar block geometry while, the DSM of the tunnel is created using automatic image correlation techniques. The geomechanical data are sampled on the DSM, by using the acquired images in a GUI and a segmentation procedure to select discontinuity planes. To allow an easier and faster identification of relevant features of the surface of the tunnel, using again an automatic procedure, an orthophoto of the tunnel is produced. A case study where a tunnel section of ca. 130 m has been surveyed is presented.

Research on the Automatic Fusion Strategy of Fixed Value Boundary Based on the Weak Coupling Condition of Grid Partition

NASA Astrophysics Data System (ADS)

Wang, X. Y.; Dou, J. M.; Shen, H.; Li, J.; Yang, G. S.; Fan, R. Q.; Shen, Q.

2018-03-01

With the continuous strengthening of power grids, the network structure is becoming more and more complicated. An open and regional data modeling is used to complete the calculation of the protection fixed value based on the local region. At the same time, a high precision, quasi real-time boundary fusion technique is needed to seamlessly integrate the various regions so as to constitute an integrated fault computing platform which can conduct transient stability analysis of covering the whole network with high accuracy and multiple modes, deal with the impact results of non-single fault, interlocking fault and build “the first line of defense” of the power grid. The boundary fusion algorithm in this paper is an automatic fusion algorithm based on the boundary accurate coupling of the networking power grid partition, which takes the actual operation mode for qualification, complete the boundary coupling algorithm of various weak coupling partition based on open-loop mode, improving the fusion efficiency, truly reflecting its transient stability level, and effectively solving the problems of too much data, too many difficulties of partition fusion, and no effective fusion due to mutually exclusive conditions. In this paper, the basic principle of fusion process is introduced firstly, and then the method of boundary fusion customization is introduced by scene description. Finally, an example is given to illustrate the specific algorithm on how it effectively implements the boundary fusion after grid partition and to verify the accuracy and efficiency of the algorithm.

Shape design sensitivity analysis and optimization of three dimensional elastic solids using geometric modeling and automatic regridding. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Yao, Tse-Min; Choi, Kyung K.

1987-01-01

An automatic regridding method and a three dimensional shape design parameterization technique were constructed and integrated into a unified theory of shape design sensitivity analysis. An algorithm was developed for general shape design sensitivity analysis of three dimensional eleastic solids. Numerical implementation of this shape design sensitivity analysis method was carried out using the finite element code ANSYS. The unified theory of shape design sensitivity analysis uses the material derivative of continuum mechanics with a design velocity field that represents shape change effects over the structural design. Automatic regridding methods were developed by generating a domain velocity field with boundary displacement method. Shape design parameterization for three dimensional surface design problems was illustrated using a Bezier surface with boundary perturbations that depend linearly on the perturbation of design parameters. A linearization method of optimization, LINRM, was used to obtain optimum shapes. Three examples from different engineering disciplines were investigated to demonstrate the accuracy and versatility of this shape design sensitivity analysis method.

Automatic variable selection method and a comparison for quantitative analysis in laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Duan, Fajie; Fu, Xiao; Jiang, Jiajia; Huang, Tingting; Ma, Ling; Zhang, Cong

2018-05-01

In this work, an automatic variable selection method for quantitative analysis of soil samples using laser-induced breakdown spectroscopy (LIBS) is proposed, which is based on full spectrum correction (FSC) and modified iterative predictor weighting-partial least squares (mIPW-PLS). The method features automatic selection without artificial processes. To illustrate the feasibility and effectiveness of the method, a comparison with genetic algorithm (GA) and successive projections algorithm (SPA) for different elements (copper, barium and chromium) detection in soil was implemented. The experimental results showed that all the three methods could accomplish variable selection effectively, among which FSC-mIPW-PLS required significantly shorter computation time (12 s approximately for 40,000 initial variables) than the others. Moreover, improved quantification models were got with variable selection approaches. The root mean square errors of prediction (RMSEP) of models utilizing the new method were 27.47 (copper), 37.15 (barium) and 39.70 (chromium) mg/kg, which showed comparable prediction effect with GA and SPA.

PET Index of Bone Glucose Metabolism (PIBGM) Classification of PET/CT Data for Fever of Unknown Origin Diagnosis

PubMed Central

Yang, Jian; Liu, Xinxin; Ai, Danni; Fan, Jingfan; Zheng, Youjing; Li, Fang; Huo, Li; Wang, Yongtian

2015-01-01

Objectives Fever of unknown origin (FUO) remains a challenge in clinical practice. Fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) is helpful in diagnosing the etiology of FUO. This paper aims to develop a completely automatic classification method based on PET/CT data for the computer-assisted diagnosis of FUO. Methods We retrospectively analyzed the FDG PET/CT scan of 175 FUO patients, 79 males and 96 females. The final diagnosis of all FUO patients was achieved through pathology or clinical evaluation, including 108 normal patients and 67 FUO patients. CT anatomic information was used to acquire bone functional information from PET images. The skeletal system of FUO patients was classified by analyzing the standardized uptake value (SUV) and the PET index of bone glucose metabolism (PIBGM). The SUV distributions in the bone marrow and the bone cortex were also studied in detail. Results The SUV and PIBGM of the bone marrow only slightly differed between the FUO patients and normal people, whereas the SUV of whole bone structures and the PIBGM of the bone cortex significantly differed between the normal people and FUO patients. The method detected 43 patients from 67 FUO patients, with sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 64.18%, 95%, 93.48%, 72.73%, and 83.33%, respectively. Conclusion The experimental results demonstrate that the study can achieve automatic classification of FUO patients by the proposed novel biomarker of PIBGM, which has the potential to be utilized in clinical practice. PMID:26076139

Automatic partitioning of head CTA for enabling segmentation

NASA Astrophysics Data System (ADS)

Suryanarayanan, Srikanth; Mullick, Rakesh; Mallya, Yogish; Kamath, Vidya; Nagaraj, Nithin

2004-05-01

Radiologists perform a CT Angiography procedure to examine vascular structures and associated pathologies such as aneurysms. Volume rendering is used to exploit volumetric capabilities of CT that provides complete interactive 3-D visualization. However, bone forms an occluding structure and must be segmented out. The anatomical complexity of the head creates a major challenge in the segmentation of bone and vessel. An analysis of the head volume reveals varying spatial relationships between vessel and bone that can be separated into three sub-volumes: "proximal", "middle", and "distal". The "proximal" and "distal" sub-volumes contain good spatial separation between bone and vessel (carotid referenced here). Bone and vessel appear contiguous in the "middle" partition that remains the most challenging region for segmentation. The partition algorithm is used to automatically identify these partition locations so that different segmentation methods can be developed for each sub-volume. The partition locations are computed using bone, image entropy, and sinus profiles along with a rule-based method. The algorithm is validated on 21 cases (varying volume sizes, resolution, clinical sites, pathologies) using ground truth identified visually. The algorithm is also computationally efficient, processing a 500+ slice volume in 6 seconds (an impressive 0.01 seconds / slice) that makes it an attractive algorithm for pre-processing large volumes. The partition algorithm is integrated into the segmentation workflow. Fast and simple algorithms are implemented for processing the "proximal" and "distal" partitions. Complex methods are restricted to only the "middle" partition. The partitionenabled segmentation has been successfully tested and results are shown from multiple cases.