126 resultados para facial fracture


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In automatic facial expression recognition, an increasing number of techniques had been proposed for in the literature that exploits the temporal nature of facial expressions. As all facial expressions are known to evolve over time, it is crucially important for a classifier to be capable of modelling their dynamics. We establish that the method of sparse representation (SR) classifiers proves to be a suitable candidate for this purpose, and subsequently propose a framework for expression dynamics to be efficiently incorporated into its current formulation. We additionally show that for the SR method to be applied effectively, then a certain threshold on image dimensionality must be enforced (unlike in facial recognition problems). Thirdly, we determined that recognition rates may be significantly influenced by the size of the projection matrix \Phi. To demonstrate these, a battery of experiments had been conducted on the CK+ dataset for the recognition of the seven prototypic expressions - anger, contempt, disgust, fear, happiness, sadness and surprise - and comparisons have been made between the proposed temporal-SR against the static-SR framework and state-of-the-art support vector machine.

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This study aimed to clarify the relationship between the mechanical environment at the fracture site and endogenous fibroblast growth factor-2 (FGF-2). We compared two types of fracture healing with different callus formations and cellular events using MouseFix(TM) plate fixation systems for murine fracture models. Left femoral fractures were induced in 72 ten-week-old mice and then fixed with a flexible (Group F) or rigid (Group R) Mouse Fix(TM) plate. Mice were sacrificed on days 3, 5, 7, 10, 14, and 21. The callus volumes were measured by 3D micro-CT and tissues were histologically stained with hematoxylin & eosin or safranin-O. Sections from days 3, 5, and 7 were immunostained for FGF-2 and Proliferating Cell Nuclear Antigen (PCNA). The callus in Group F was significantly larger than that in Group R. The rigid plate allowed bone union without a marked external callus or chondrogenesis. The flexible plate formed a large external callus as a result of endochondral ossification. Fibroblastic cells in the granulation tissue on days 5 and 7 in Group F showed marked FGF-2 expression compared with Group R. Fibroblastic cells showed ongoing proliferation in granulation tissue in group F, as indicated by PCNA expression, which explained the relative granulation tissue increase in group F. There were major differences in early phase endogenous FGF-2 expression between these two fracture healing processes, due to different mechanical environments.

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Virtual methods to assess the fitting of a fracture fixation plate were proposed recently, however with limitations such as simplified fit criteria or manual data processing. This study aims to automate a fit analysis procedure using clinical-based criteria, and then to analyse the results further for borderline fit cases. Three dimensional (3D) models of 45 bones and of a precontoured distal tibial plate were utilized to assess the fitting of the plate automatically. A Matlab program was developed to automatically measure the shortest distance between the bone and the plate at three regions of interest and a plate-bone angle. The measured values including the fit assessment results were recorded in a spreadsheet as part of the batch-process routine. An automated fit analysis procedure will enable the processing of larger bone datasets in a significantly shorter time, which will provide more representative data of the target population for plate shape design and validation. As a result, better fitting plates can be manufactured and made available to surgeons, thereby reducing the risk and cost associated with complications or corrective procedures. This in turn, is expected to translate into improving patients' quality of life.

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The present study investigated whether facial expressions of emotion presented outside consciousness awareness will elicit evaluative responses as assessed in affective priming. Participants were asked to evaluate pleasant and unpleasant target words that were preceded by masked or unmasked schematic (Experiment 1) or photographic faces (Experiments 1 and 2) with happy or angry expressions. They were either required to perform the target evaluation only or to perform the target evaluation and to name the emotion expressed by the face prime. Prime-target interval was 300 ms in Experiment 1 and 80 ms in Experiment 2. Naming performance confirmed the effectiveness of the masking procedure. Affective priming was evident after unmasked primes in tasks that required naming of the facial expressions for schematic and photographic faces and after unmasked primes in tasks that did not require naming for photographic faces. No affective priming was found after masked primes. The present study failed to provide evidence for affective priming with masked face primes, however, it indicates that voluntary attention to the primes enhances affective priming.

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Feature extraction and selection are critical processes in developing facial expression recognition (FER) systems. While many algorithms have been proposed for these processes, direct comparison between texture, geometry and their fusion, as well as between multiple selection algorithms has not been found for spontaneous FER. This paper addresses this issue by proposing a unified framework for a comparative study on the widely used texture (LBP, Gabor and SIFT) and geometric (FAP) features, using Adaboost, mRMR and SVM feature selection algorithms. Our experiments on the Feedtum and NVIE databases demonstrate the benefits of fusing geometric and texture features, where SIFT+FAP shows the best performance, while mRMR outperforms Adaboost and SVM. In terms of computational time, LBP and Gabor perform better than SIFT. The optimal combination of SIFT+FAP+mRMR also exhibits a state-of-the-art performance.

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Large margin learning approaches, such as support vector machines (SVM), have been successfully applied to numerous classification tasks, especially for automatic facial expression recognition. The risk of such approaches however, is their sensitivity to large margin losses due to the influence from noisy training examples and outliers which is a common problem in the area of affective computing (i.e., manual coding at the frame level is tedious so coarse labels are normally assigned). In this paper, we leverage the relaxation of the parallel-hyperplanes constraint and propose the use of modified correlation filters (MCF). The MCF is similar in spirit to SVMs and correlation filters, but with the key difference of optimizing only a single hyperplane. We demonstrate the superiority of MCF over current techniques on a battery of experiments.

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Bone’s capacity to repair following trauma is both unique and astounding. However, fractures sometimes fail to heal. Hence, the goal of fracture treatment is the restoration of bone’s structure, composition and function. Fracture fixation devices should provide a favourable mechanical and biological environment for healing to occur. The use of internal fixation is increasing as these devices may be applied with less invasive techniques. Recent studies suggest however that, internal fixation devices may be overly stiff and suppresses callus formation. The degree of mechanical stability influences the healing outcome. This is determined by the stiffness of the fixation device and the degree of limb loading. This project aims to characterise the fixation stability of an internal plate fixation device and the influence of modifications to its configuration on implant stability. As there are no standardised methods for the determination of fixation stiffness, the first part of this project aims to compares different methodologies and determines the most appropriate method to characterise the stiffness of internal plate fixators. The stiffness of a fixation device also influences the physiological loads experienced by the healing bone. Since bone adapts to this applied load by undergoing changes through a remodelling process, undesirable changes could occur during the period of treatment with an implant. The second part of this project aims to develop a methodology to quantify remodelling changes. This quantification is expected to aid our understanding of the changes in pattern due to implant related remodelling and on the factors driving the remodelling process. Knowledge gained in this project is useful to understand how the configuration of internal fixation devices can promote timely healing and prevent undesirable bone loss.

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Mechanically well-defined stabilization systems have only recently become available, providing standardized conditions for studying the role of the mechanical environment on mouse bone fracture healing. The aim of this study was to characterize the time course of strength recovery and callus development of mouse femoral osteotomies stabilized with either low or high flexibility (in bending and torsion) internal fixation plates. Animals were euthanized and femora excised at 14, 21, and 28 days post-osteotomy for microCT analysis and torsional strength testing. While a larger mineralized callus was observed in osteotomies under more flexible conditions at all time points, the earlier bridging of the mineralized callus under less flexible conditions by 1 week resulted in an earlier recovery of torsional strength in mice stabilized with low flexibility fixation. Ultimate torque values for these bones were significantly higher at 14 and 21 days post-osteotomy compared to bones with the more flexible stabilization. Our study confirms the high reproducibility of the results that are achieved with this new implant system, therefore making it ideal for studying the influence of the mechanical environment on murine fracture healing under highly standardized conditions.

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The finite element (FE) analysis is an effective method to study the strength and predict the fracture risk of endodontically-treated teeth. This paper presents a rapid method developed to generate a comprehensive tooth FE model using data retrieved from micro-computed tomography (μCT). With this method, the inhomogeneity of material properties of teeth was included into the model without dividing the tooth model into different regions. The material properties of the tooth were assumed to be related to the mineral density. The fracture risk at different tooth portions was assessed for root canal treatments. The micro-CT images of a tooth were processed by a Matlab software programme and the CT numbers were retrieved. The tooth contours were obtained with thresholding segmentation using Amira. The inner and outer surfaces of the tooth were imported into Solidworks and a three-dimensional (3D) tooth model was constructed. An assembly of the tooth model with the periodontal ligament (PDL) layer and surrounding bone was imported into ABAQUS. The material properties of the tooth were calculated from the retrieved CT numbers via ABAQUS user's subroutines. Three root canal geometries (original and two enlargements) were investigated. The proposed method in this study can generate detailed 3D finite element models of a tooth with different root canal enlargements and filling materials, and would be very useful for the assessment of the fracture risk at different tooth portions after root canal treatments.