970 resultados para computer algorithm
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We evaluate the performance of different optimization techniques developed in the context of optical flow computation with different variational models. In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we de- velop the use of efficient multilevel schemes for computing the optical flow. More precisely, we evaluate the performance of a standard unidirectional mul- tilevel algorithm - called multiresolution optimization (MR/OPT), to a bidrec- tional multilevel algorithm - called full multigrid optimization (FMG/OPT). The FMG/OPT algorithm treats the coarse grid correction as an optimiza- tion search direction and eventually scales it using a line search. Experimental results on different image sequences using four models of optical flow com- putation show that the FMG/OPT algorithm outperforms both the TN and MR/OPT algorithms in terms of the computational work and the quality of the optical flow estimation.
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The atomic force microscope is not only a very convenient tool for studying the topography of different samples, but it can also be used to measure specific binding forces between molecules. For this purpose, one type of molecule is attached to the tip and the other one to the substrate. Approaching the tip to the substrate allows the molecules to bind together. Retracting the tip breaks the newly formed bond. The rupture of a specific bond appears in the force-distance curves as a spike from which the binding force can be deduced. In this article we present an algorithm to automatically process force-distance curves in order to obtain bond strength histograms. The algorithm is based on a fuzzy logic approach that permits an evaluation of "quality" for every event and makes the detection procedure much faster compared to a manual selection. In this article, the software has been applied to measure the binding strength between tubuline and microtubuline associated proteins.
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Background: The first AO comprehensive pediatric long bone fracture classification system has been established following a structured path of development and validation with experienced pediatric surgeons. Methods: A follow-up series of agreement studies was applied to specify and evaluate a grading system for displacement of pediatric supracondylar fractures. An iterative process comprising an international group of 5 experienced pediatric surgeons (Phase 1) followed by a pragmatic multicenter agreement study involving 26 raters (Phase 2) was used. The last evaluations were conducted on a consecutive collection of 154 supracondylar fractures documented by standard anteroposterior and lateral radiographs. Results: Fractures were classified according to 1 of 4 grades: I = incomplete fracture with no or minimal displacement; II = Incomplete fracture with continuity of the posterior (extension fracture) or anterior cortex (flexion fracture); III = lack of bone continuity (broken cortex), but still some contact between the fracture planes; IV = complete fracture with no bone continuity (broken cortex), and no contact between the fracture planes. A diagnostic algorithm to support the practical application of the grading system in a clinical setting, as well as an aid using a circle placed over the capitellum was proposed. The overall kappa coefficients were 0.68 and 0.61 in the Phase 1 and Phase 2 studies, respectively. In the Phase 1 study, fracture grades I, II, III, and IV were classified with median accuracies of 91%, 82%, 83%, and 99.5%, respectively. Similar median accuracies of 86% (Grade I), 73% (Grade II), 83%(Grade III), and 92% were reported for the Phase 2 study. Reliability was high in distinguishing complete, unstable fractures from stable injuries [ie, kappa coefficients of 0.84 (Phase 1) and 0.83 (Phase 2) were calculated]; in Phase 2, surgeons' accuracies in classifying complete fractures were all above 85%. Conclusions: With clear and unambiguous definition, this new grading system for supracondylar fracture displacement has proved to be sufficiently reliable and accurate when applied by pediatric surgeons in the framework of clinical routine as well as research.
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Background: Research in epistasis or gene-gene interaction detection for human complex traits has grown over the last few years. It has been marked by promising methodological developments, improved translation efforts of statistical epistasis to biological epistasis and attempts to integrate different omics information sources into the epistasis screening to enhance power. The quest for gene-gene interactions poses severe multiple-testing problems. In this context, the maxT algorithm is one technique to control the false-positive rate. However, the memory needed by this algorithm rises linearly with the amount of hypothesis tests. Gene-gene interaction studies will require a memory proportional to the squared number of SNPs. A genome-wide epistasis search would therefore require terabytes of memory. Hence, cache problems are likely to occur, increasing the computation time. In this work we present a new version of maxT, requiring an amount of memory independent from the number of genetic effects to be investigated. This algorithm was implemented in C++ in our epistasis screening software MBMDR-3.0.3. We evaluate the new implementation in terms of memory efficiency and speed using simulated data. The software is illustrated on real-life data for Crohn’s disease. Results: In the case of a binary (affected/unaffected) trait, the parallel workflow of MBMDR-3.0.3 analyzes all gene-gene interactions with a dataset of 100,000 SNPs typed on 1000 individuals within 4 days and 9 hours, using 999 permutations of the trait to assess statistical significance, on a cluster composed of 10 blades, containing each four Quad-Core AMD Opteron(tm) Processor 2352 2.1 GHz. In the case of a continuous trait, a similar run takes 9 days. Our program found 14 SNP-SNP interactions with a multiple-testing corrected p-value of less than 0.05 on real-life Crohn’s disease (CD) data. Conclusions: Our software is the first implementation of the MB-MDR methodology able to solve large-scale SNP-SNP interactions problems within a few days, without using much memory, while adequately controlling the type I error rates. A new implementation to reach genome-wide epistasis screening is under construction. In the context of Crohn’s disease, MBMDR-3.0.3 could identify epistasis involving regions that are well known in the field and could be explained from a biological point of view. This demonstrates the power of our software to find relevant phenotype-genotype higher-order associations.
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The Learning Affect Monitor (LAM) is a new computer-based assessment system integrating basic dimensional evaluation and discrete description of affective states in daily life, based on an autonomous adapting system. Subjects evaluate their affective states according to a tridimensional space (valence and activation circumplex as well as global intensity) and then qualify it using up to 30 adjective descriptors chosen from a list. The system gradually adapts to the user, enabling the affect descriptors it presents to be increasingly relevant. An initial study with 51 subjects, using a 1 week time-sampling with 8 to 10 randomized signals per day, produced n = 2,813 records with good reliability measures (e.g., response rate of 88.8%, mean split-half reliability of .86), user acceptance, and usability. Multilevel analyses show circadian and hebdomadal patterns, and significant individual and situational variance components of the basic dimension evaluations. Validity analyses indicate sound assignment of qualitative affect descriptors in the bidimensional semantic space according to the circumplex model of basic affect dimensions. The LAM assessment module can be implemented on different platforms (palm, desk, mobile phone) and provides very rapid and meaningful data collection, preserving complex and interindividually comparable information in the domain of emotion and well-being.
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It is well known the relationship between source separation and blind deconvolution: If a filtered version of an unknown i.i.d. signal is observed, temporal independence between samples can be used to retrieve the original signal, in the same manner as spatial independence is used for source separation. In this paper we propose the use of a Genetic Algorithm (GA) to blindly invert linear channels. The use of GA is justified in the case of small number of samples, where other gradient-like methods fails because of poor estimation of statistics.
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A computer program to adjust roadway profiles has been developed to serve as an aid to the county engineers of the State of Iowa. Many hours are spent reducing field notes and calculating adjusted roadway profiles to prepare an existing roadway for paving that will produce a high quality ride and be as maintenance free as possible. Since the computer is very well adapted to performing long tedious tasks; programming this work for a computer would result in freeing the engineer of these tasks. Freed from manual calculations, the engineer is able to spend more time in solving engineering problems. The type of roadway that this computer program is designed to adjust is a road that at sometime. in its history was graded to a finished subgrade. After a period of time, this road is to receive a finished paved surface. The problem then arises whether to bring the existing roadway up to the de signed grade or to make profile adjustments and comprise between the existing and the design profiles. In order to achieve the latter condition using this program, the engineer needs to give the computer only a minimum amount of information.
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Report on selected computer systems operated by the State of Iowa for the period July 1, 1999 through June 30, 2014
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This project was undertaken in coordination with the Environmental Assessment process on the Mt. Vernon Road Improvements project in Cedar Rapids, Iowa. The goal of the research was to determine the cost effectiveness of combined photo-imaging and computer animation as a presentation tool describing public road improvements. The Public Hearing, in combination with the involvement of a Citizen's Resource Group, afforded an opportunity to have an evaluation of the processes by interested citizens who were not familiar with engineering drawings or the construction industry. After the initial viewing of a draft version of the video, the Resource Group made recommendations to the staff developing the video. Discussion of these recommendations led to the development of an animated composite section that showed a combination of situations typically encountered throughout the project corridor, as well as critical considerations. The composite section did not show specific locations and therefore, individuals were not distracted by looking for the details pertaining to their properties. Concentration on the concepts involved rather than specifics provided the opportunity for a more thorough understanding by the citizens. The development of the composite concept was the primary discovery of the research.
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Context: Ovarian tumors (OT) typing is a competency expected from pathologists, with significant clinical implications. OT however come in numerous different types, some rather rare, with the consequence of few opportunities for practice in some departments. Aim: Our aim was to design a tool for pathologists to train in less common OT typing. Method and Results: Representative slides of 20 less common OT were scanned (Nano Zoomer Digital Hamamatsu®) and the diagnostic algorithm proposed by Young and Scully applied to each case (Young RH and Scully RE, Seminars in Diagnostic Pathology 2001, 18: 161-235) to include: recognition of morphological pattern(s); shortlisting of differential diagnosis; proposition of relevant immunohistochemical markers. The next steps of this project will be: evaluation of the tool in several post-graduate training centers in Europe and Québec; improvement of its design based on evaluation results; diffusion to a larger public. Discussion: In clinical medicine, solving many cases is recognized as of utmost importance for a novice to become an expert. This project relies on the virtual slides technology to provide pathologists with a learning tool aimed at increasing their skills in OT typing. After due evaluation, this model might be extended to other uncommon tumors.
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Positron emission computed tomography (PET) is a functional, noninvasive method for imaging regional metabolic processes that is nowadays most often combined to morphological imaging with computed tomography (CT). Its use is based on the well-founded assumption that metabolic changes occur earlier in tumors than morphologic changes, adding another dimension to imaging. This article will review the established and investigational indications and radiopharmaceuticals for PET/CT imaging for prostate cancer, bladder cancer and testicular cancer, before presenting upcoming applications in radiation therapy.
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This paper proposes an automatic hand detection system that combines the Fourier-Mellin Transform along with other computer vision techniques to achieve hand detection in cluttered scene color images. The proposed system uses the Fourier-Mellin Transform as an invariant feature extractor to perform RST invariant hand detection. In a first stage of the system a simple non-adaptive skin color-based image segmentation and an interest point detector based on corners are used in order to identify regions of interest that contains possible matches. A sliding window algorithm is then used to scan the image at different scales performing the FMT calculations only in the previously detected regions of interest and comparing the extracted FM descriptor of the windows with a hand descriptors database obtained from a train image set. The results of the performed experiments suggest the use of Fourier-Mellin invariant features as a promising approach for automatic hand detection.
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Computer-Aided Tomography Angiography (CTA) images are the standard for assessing Peripheral artery disease (PAD). This paper presents a Computer Aided Detection (CAD) and Computer Aided Measurement (CAM) system for PAD. The CAD stage detects the arterial network using a 3D region growing method and a fast 3D morphology operation. The CAM stage aims to accurately measure the artery diameters from the detected vessel centerline, compensating for the partial volume effect using Expectation Maximization (EM) and a Markov Random field (MRF). The system has been evaluated on phantom data and also applied to fifteen (15) CTA datasets, where the detection accuracy of stenosis was 88% and the measurement accuracy was with an 8% error.
Resumo:
This paper proposes an automatic hand detection system that combines the Fourier-Mellin Transform along with other computer vision techniques to achieve hand detection in cluttered scene color images. The proposed system uses the Fourier-Mellin Transform as an invariant feature extractor to perform RST invariant hand detection. In a first stage of the system a simple non-adaptive skin color-based image segmentation and an interest point detector based on corners are used in order to identify regions of interest that contains possible matches. A sliding window algorithm is then used to scan the image at different scales performing the FMT calculations only in the previously detected regions of interest and comparing the extracted FM descriptor of the windows with a hand descriptors database obtained from a train image set. The results of the performed experiments suggest the use of Fourier-Mellin invariant features as a promising approach for automatic hand detection.