236 resultados para segment QT


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Footwear is designed to reduce injury, and enhance performance. However, the effect footwear has on foot and ankle kinematics currently remains unknown. Acknowledging the need for improved understanding, multi-segment models of the foot-shoe complex need to be established to both describe and quantify the effect footwear has on the foot and ankle during stance phase of gait. The purpose of this study was to quantify how footwear alters the kinematics of the foot inside the shoe during stance phase of walking gait.

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Finite element analyses of the human body in seated postures requires digital models capable of providing accurate and precise prediction of the tissue-level response of the body in the seated posture. To achieve such models, the human anatomy must be represented with high fidelity. This information can readily be defined using medical imaging techniques such as Magnetic Resonance Imaging (MRI) or Computed Tomography (CT). Current practices for constructing digital human models, based on the magnetic resonance (MR) images, in a lying down (supine) posture have reduced the error in the geometric representation of human anatomy relative to reconstructions based on data from cadaveric studies. Nonetheless, the significant differences between seated and supine postures in segment orientation, soft-tissue deformation and soft tissue strain create a need for data obtained in postures more similar to the application posture. In this study, we present a novel method for creating digital human models based on seated MR data. An adult-male volunteer was scanned in a simulated driving posture using a FONAR 0.6T upright MRI scanner with a T1 scanning protocol. To compensate for unavoidable image distortion near the edges of the study, images of the same anatomical structures were obtained in transverse and sagittal planes. Combinations of transverse and sagittal images were used to reconstruct the major anatomical features from the buttocks through the knees, including bone, muscle and fat tissue perimeters, using Solidworks® software. For each MR image, B-splines were created as contours for the anatomical structures of interest, and LOFT commands were used to interpolate between the generated Bsplines. The reconstruction of the pelvis, from MR data, was enhanced by the use of a template model generated in previous work CT images. A non-rigid registration algorithm was used to fit the pelvis template into the MR data. Additionally, MR image processing was conducted to both the left and the right sides of the model due to the intended asymmetric posture of the volunteer during the MR measurements. The presented subject-specific, three-dimensional model of the buttocks and thighs will add value to optimisation cycles in automotive seat development when used in simulating human interaction with automotive seats.

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Virtual prototyping emerges as a new technology to replace existing physical prototypes for product evaluation, which are costly and time consuming to manufacture. Virtualization technology allows engineers and ergonomists to perform virtual builds and different ergonomic analyses on a product. Digital Human Modelling (DHM) software packages such as Siemens Jack, often integrate with CAD systems to provide a virtual environment which allows investigation of operator and product compatibility. Although the integration between DHM and CAD systems allows for the ergonomic analysis of anthropometric design, human musculoskeletal, multi-body modelling software packages such as the AnyBody Modelling System (AMS) are required to support physiologic design. They provide muscular force analysis, estimate human musculoskeletal strain and help address human comfort assessment. However, the independent characteristics of the modelling systems Jack and AMS constrain engineers and ergonomists in conducting a complete ergonomic analysis. AMS is a stand alone programming system without a capability to integrate into CAD environments. Jack is providing CAD integrated human-in-the-loop capability, but without considering musculoskeletal activity. Consequently, engineers and ergonomists need to perform many redundant tasks during product and process design. Besides, the existing biomechanical model in AMS uses a simplified estimation of body proportions, based on a segment mass ratio derived scaling approach. This is insufficient to represent user populations anthropometrically correct in AMS. In addition, sub-models are derived from different sources of morphologic data and are therefore anthropometrically inconsistent. Therefore, an interface between the biomechanical AMS and the virtual human model Jack was developed to integrate a musculoskeletal simulation with Jack posture modeling. This interface provides direct data exchange between the two man-models, based on a consistent data structure and common body model. The study assesses kinematic and biomechanical model characteristics of Jack and AMS, and defines an appropriate biomechanical model. The information content for interfacing the two systems is defined and a protocol is identified. The interface program is developed and implemented through Tcl and Jack-script(Python), and interacts with the AMS console application to operate AMS procedures.

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Finite Element Modeling (FEM) has become a vital tool in the automotive design and development processes. FEM of the human body is a technique capable of estimating parameters that are difficult to measure in experimental studies with the human body segments being modeled as complex and dynamic entities. Several studies have been dedicated to attain close-to-real FEMs of the human body (Pankoke and Siefert 2007; Amann, Huschenbeth et al. 2009; ESI 2010). The aim of this paper is to identify and appraise the state of-the art models of the human body which incorporate detailed pelvis and/or lower extremity models. Six databases and search engines were used to obtain literature, and the search was limited to studies published in English since 2000. The initial search results identified 636 pelvis-related papers, 834 buttocks-related papers, 505 thigh-related papers, 927 femur-related papers, 2039 knee-related papers, 655 shank-related papers, 292 tibia-related papers, 110 fibula-related papers, 644 ankle related papers, and 5660 foot-related papers. A refined search returned 100 pelvis-related papers, 45 buttocks related papers, 65 thigh-related papers, 162 femur-related papers, 195 kneerelated papers, 37 shank-related papers, 80 tibia-related papers, 30 fibula-related papers and 102 ankle-related papers and 246 foot-related papers. The refined literature list was further restricted by appraisal against a modified LOW appraisal criteria. Studies with unclear methodologies, with a focus on populations with pathology or with sport related dynamic motion modeling were excluded. The final literature list included fifteen models and each was assessed against the percentile the model represents, the gender the model was based on, the human body segment/segments included in the model, the sample size used to develop the model, the source of geometric/anthropometric values used to develop the model, the posture the model represents and the finite element solver used for the model. The results of this literature review provide indication of bias in the available models towards 50th percentile male modeling with a notable concentration on the pelvis, femur and buttocks segments.

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In information retrieval (IR) research, more and more focus has been placed on optimizing a query language model by detecting and estimating the dependencies between the query and the observed terms occurring in the selected relevance feedback documents. In this paper, we propose a novel Aspect Language Modeling framework featuring term association acquisition, document segmentation, query decomposition, and an Aspect Model (AM) for parameter optimization. Through the proposed framework, we advance the theory and practice of applying high-order and context-sensitive term relationships to IR. We first decompose a query into subsets of query terms. Then we segment the relevance feedback documents into chunks using multiple sliding windows. Finally we discover the higher order term associations, that is, the terms in these chunks with high degree of association to the subsets of the query. In this process, we adopt an approach by combining the AM with the Association Rule (AR) mining. In our approach, the AM not only considers the subsets of a query as “hidden” states and estimates their prior distributions, but also evaluates the dependencies between the subsets of a query and the observed terms extracted from the chunks of feedback documents. The AR provides a reasonable initial estimation of the high-order term associations by discovering the associated rules from the document chunks. Experimental results on various TREC collections verify the effectiveness of our approach, which significantly outperforms a baseline language model and two state-of-the-art query language models namely the Relevance Model and the Information Flow model

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The complex interaction of the bones of the foot has been explored in detail in recent years, which has led to the acknowledgement in the biomechanics community that the foot can no longer be considered as a single rigid segment. With the advance of motion analysis technology it has become possible to quantify the biomechanics of simplified units or segments that make up the foot. Advances in technology coupled with reducing hardware prices has resulted in the uptake of more advanced tools available for clinical gait analysis. The increased use of these techniques in clinical practice requires defined standards for modelling and reporting of foot and ankle kinematics. This systematic review aims to provide a critical appraisal of commonly used foot and ankle marker sets designed to assess kinematics and thus provide a theoretical background for the development of modelling standards.

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Footwear is designed to reduce injury and enhance performance. However, the effect footwear has on foot and ankle kinematics currently remains unknown. Acknowledging the need for improved understanding, the aim of this study was to describe the effect footwear has on the kinematics of a multi segment foot during stance phase of walking gait.

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Magnetic Resonance Imaging was used to study changes in the crystalline lens and ciliary body with accommodation and aging. Monocular images were obtained in 15 young (19-29 years) and 15 older (60-70 years) emmetropes when viewing at far (6m) and at individual near points (14.5 to 20.9 cm) in the younger group. With accommodation, lens thickness increased (mean±95% CI: 0.33±0.06mm) by a similar magnitude to the decrease in anterior chamber depth (0.31±0.07mm) and equatorial diameter (0.32±0.04mm) with a decrease in the radius of curvature of the posterior lens surface (0.58±0.30mm). Anterior lens surface shape could not be determined due to the overlapping region with the iris. Ciliary ring diameter decreased (0.44±0.17mm) with no decrease in circumlental space or forward ciliary body movement. With aging, lens thickness increased (mean±95% CI: 0.97±0.24mm) similar in magnitude to the sum of the decrease in anterior chamber depth (0.45±0.21mm) and increase in anterior segment depth (0.52±0.23mm). Equatorial lens diameter increased (0.28±0.23mm) with no change in the posterior lens surface radius of curvature. Ciliary ring diameter decreased (0.57±0.41mm) with reduced circumlental space (0.43±0.15mm) and no forward ciliary body movement. Accommodative changes support the Helmholtz theory of accommodation including an increase in posterior lens surface curvature. Certain aspects of aging changes mimic accommodation.

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Accurate and detailed road models play an important role in a number of geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance systems. In this thesis, an integrated approach for the automatic extraction of precise road features from high resolution aerial images and LiDAR point clouds is presented. A framework of road information modeling has been proposed, for rural and urban scenarios respectively, and an integrated system has been developed to deal with road feature extraction using image and LiDAR analysis. For road extraction in rural regions, a hierarchical image analysis is first performed to maximize the exploitation of road characteristics in different resolutions. The rough locations and directions of roads are provided by the road centerlines detected in low resolution images, both of which can be further employed to facilitate the road information generation in high resolution images. The histogram thresholding method is then chosen to classify road details in high resolution images, where color space transformation is used for data preparation. After the road surface detection, anisotropic Gaussian and Gabor filters are employed to enhance road pavement markings while constraining other ground objects, such as vegetation and houses. Afterwards, pavement markings are obtained from the filtered image using the Otsu's clustering method. The final road model is generated by superimposing the lane markings on the road surfaces, where the digital terrain model (DTM) produced by LiDAR data can also be combined to obtain the 3D road model. As the extraction of roads in urban areas is greatly affected by buildings, shadows, vehicles, and parking lots, we combine high resolution aerial images and dense LiDAR data to fully exploit the precise spectral and horizontal spatial resolution of aerial images and the accurate vertical information provided by airborne LiDAR. Objectoriented image analysis methods are employed to process the feature classiffcation and road detection in aerial images. In this process, we first utilize an adaptive mean shift (MS) segmentation algorithm to segment the original images into meaningful object-oriented clusters. Then the support vector machine (SVM) algorithm is further applied on the MS segmented image to extract road objects. Road surface detected in LiDAR intensity images is taken as a mask to remove the effects of shadows and trees. In addition, normalized DSM (nDSM) obtained from LiDAR is employed to filter out other above-ground objects, such as buildings and vehicles. The proposed road extraction approaches are tested using rural and urban datasets respectively. The rural road extraction method is performed using pan-sharpened aerial images of the Bruce Highway, Gympie, Queensland. The road extraction algorithm for urban regions is tested using the datasets of Bundaberg, which combine aerial imagery and LiDAR data. Quantitative evaluation of the extracted road information for both datasets has been carried out. The experiments and the evaluation results using Gympie datasets show that more than 96% of the road surfaces and over 90% of the lane markings are accurately reconstructed, and the false alarm rates for road surfaces and lane markings are below 3% and 2% respectively. For the urban test sites of Bundaberg, more than 93% of the road surface is correctly reconstructed, and the mis-detection rate is below 10%.

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The design of pre-contoured fracture fixation implants (plates and nails) that correctly fit the anatomy of a patient utilises 3D models of long bones with accurate geometric representation. 3D data is usually available from computed tomography (CT) scans of human cadavers that generally represent the above 60 year old age group. Thus, despite the fact that half of the seriously injured population comes from the 30 year age group and below, virtually no data exists from these younger age groups to inform the design of implants that optimally fit patients from these groups. Hence, relevant bone data from these age groups is required. The current gold standard for acquiring such data–CT–involves ionising radiation and cannot be used to scan healthy human volunteers. Magnetic resonance imaging (MRI) has been shown to be a potential alternative in the previous studies conducted using small bones (tarsal bones) and parts of the long bones. However, in order to use MRI effectively for 3D reconstruction of human long bones, further validations using long bones and appropriate reference standards are required. Accurate reconstruction of 3D models from CT or MRI data sets requires an accurate image segmentation method. Currently available sophisticated segmentation methods involve complex programming and mathematics that researchers are not trained to perform. Therefore, an accurate but relatively simple segmentation method is required for segmentation of CT and MRI data. Furthermore, some of the limitations of 1.5T MRI such as very long scanning times and poor contrast in articular regions can potentially be reduced by using higher field 3T MRI imaging. However, a quantification of the signal to noise ratio (SNR) gain at the bone - soft tissue interface should be performed; this is not reported in the literature. As MRI scanning of long bones has very long scanning times, the acquired images are more prone to motion artefacts due to random movements of the subject‟s limbs. One of the artefacts observed is the step artefact that is believed to occur from the random movements of the volunteer during a scan. This needs to be corrected before the models can be used for implant design. As the first aim, this study investigated two segmentation methods: intensity thresholding and Canny edge detection as accurate but simple segmentation methods for segmentation of MRI and CT data. The second aim was to investigate the usability of MRI as a radiation free imaging alternative to CT for reconstruction of 3D models of long bones. The third aim was to use 3T MRI to improve the poor contrast in articular regions and long scanning times of current MRI. The fourth and final aim was to minimise the step artefact using 3D modelling techniques. The segmentation methods were investigated using CT scans of five ovine femora. The single level thresholding was performed using a visually selected threshold level to segment the complete femur. For multilevel thresholding, multiple threshold levels calculated from the threshold selection method were used for the proximal, diaphyseal and distal regions of the femur. Canny edge detection was used by delineating the outer and inner contour of 2D images and then combining them to generate the 3D model. Models generated from these methods were compared to the reference standard generated using the mechanical contact scans of the denuded bone. The second aim was achieved using CT and MRI scans of five ovine femora and segmenting them using the multilevel threshold method. A surface geometric comparison was conducted between CT based, MRI based and reference models. To quantitatively compare the 1.5T images to the 3T MRI images, the right lower limbs of five healthy volunteers were scanned using scanners from the same manufacturer. The images obtained using the identical protocols were compared by means of SNR and contrast to noise ratio (CNR) of muscle, bone marrow and bone. In order to correct the step artefact in the final 3D models, the step was simulated in five ovine femora scanned with a 3T MRI scanner. The step was corrected using the iterative closest point (ICP) algorithm based aligning method. The present study demonstrated that the multi-threshold approach in combination with the threshold selection method can generate 3D models from long bones with an average deviation of 0.18 mm. The same was 0.24 mm of the single threshold method. There was a significant statistical difference between the accuracy of models generated by the two methods. In comparison, the Canny edge detection method generated average deviation of 0.20 mm. MRI based models exhibited 0.23 mm average deviation in comparison to the 0.18 mm average deviation of CT based models. The differences were not statistically significant. 3T MRI improved the contrast in the bone–muscle interfaces of most anatomical regions of femora and tibiae, potentially improving the inaccuracies conferred by poor contrast of the articular regions. Using the robust ICP algorithm to align the 3D surfaces, the step artefact that occurred by the volunteer moving the leg was corrected, generating errors of 0.32 ± 0.02 mm when compared with the reference standard. The study concludes that magnetic resonance imaging, together with simple multilevel thresholding segmentation, is able to produce 3D models of long bones with accurate geometric representations. The method is, therefore, a potential alternative to the current gold standard CT imaging.

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The next generation of SOA needs to scale for flexible service consumption, beyond organizational boundaries and current B2B applications, into communities, eco-systems, and business networks. In the wider and, ultimately, global settings, new capabilities are needed so that business partners can efficiently and reliably enable, adapt, and expose services where they can be discovered, ordered, consumed, metered, and paid for, through new applications and opportunities, driven by third parties in the global "village". This trend is already underway, in different ways, through various early adopter market segments. For the small medium enterprises segment, Google, Intuit-Microsoft, and others have launched appstores, through which an open-ended array of hosted applications are sourced from the development community and procured as maketplace commondities. In the corporate sector, the marketplace model and business network hubs are being put in place on top of connectivity and network orchestration investments for capitalizing services as tradable assets, seen in banking/finance (e.g. American Express Intelligent Marketplace), logistics (e.g., the E2open hub), and the public sector (e.g., UK DirectGov whole-of-government citizen services delivery).

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Poem published in Free Speech segment of NTEU Newletter.

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Purpose. To investigate whether diurnal variation occurs in retinal thickness measures derived from spectral domain optical coherence tomography (SD-OCT). Methods. Twelve healthy adult subjects had retinal thickness measured with SD-OCT every 2 h over a 10 h period. At each measurement session, three average B-scan images were derived from a series of multiple B-scans (each from a 5 mm horizontal raster scan along the fovea, containing 1500 A-scans/B-scan) and analyzed to determine the thickness of the total retina, as well as the thickness of the outer retinal layers. Average thickness values were calculated at the foveal center, at the 0.5 mm diameter foveal region, and for the temporal parafovea (1.5 mm from foveal center) and nasal parafovea (1.5 mm from foveal center). Results. Total retinal thickness did not exhibit significant diurnal variation in any of the considered retinal regions (p > 0.05). Evidence of significant diurnal variation was found in the thickness of the outer retinal layers (p < 0.05), with the most prominent changes observed in the photoreceptor layers at the foveal center. The photoreceptor inner and outer segment layer thickness exhibited mean amplitude (peak to trough) of daily change of 7 ± 3 μm at the foveal center. The peak in thickness was typically observed at the third measurement session (mean measurement time, 13:06). Conclusions. The total retinal thickness measured with SD-OCT does not exhibit evidence of significant variation over the course of the day. However, small but significant diurnal variation occurs in the thickness of the foveal outer retinal layers.

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The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology(1) even in complex tissue sections(2). Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells(3), however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1). We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.

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Purpose – The purpose of this paper is to segment primary male grocery shoppers based on store and product attribute evaluations. A rich profile for each segment is developed. These developed contemporary shopper typologies are contrasted against earlier works. Design/methodology/approach – Data of 280 male grocery shoppers was attained by a survey questionnaire. Factor analysis, cluster analysis and ANOVA were employed to develop specific segments of male shoppers. Findings – Four distinct cohorts of male shoppers emerge from the data of eight constructs, measured by 46 items. One new shopper type, not found in earlier typology literature, emerged from this research. This shopper presented as young, well educated, at the commencement of their career and family lifecycle, attracted by a strong value offer and willingness to share the family food shopping responsibilities. Practical implications – Research outcomes encourage supermarket retailers to implement targeted marketing and rationalized operational strategies that deliver on attributes of importance. Originality/value – This research makes a contribution to segmentation literature and grocery retail practice in several ways. It presents the first retail typology of male supermarket shoppers, employing a cluster analysis technique. The research provides insights into the modern family food shopping behaviour of men, a channel in which men are now recognised as equal contributors. The research provides the basis for further gender comparative and cross-contextual studies.