927 resultados para Synthetic Image Analysis


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We define a pair-correlation function that can be used to characterize spatiotemporal patterning in experimental images and snapshots from discrete simulations. Unlike previous pair-correlation functions, the pair-correlation functions developed here depend on the location and size of objects. The pair-correlation function can be used to indicate complete spatial randomness, aggregation or segregation over a range of length scales, and quantifies spatial structures such as the shape, size and distribution of clusters. Comparing pair-correlation data for various experimental and simulation images illustrates their potential use as a summary statistic for calibrating discrete models of various physical processes.

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Purpose: Flat-detector, cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. Methods: The rich sources of prior information in IGRT are incorporated into a hidden Markov random field (MRF) model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk (OAR). The voxel labels are estimated using the iterated conditional modes (ICM) algorithm. Results: The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom (CIRS, Inc. model 062). The mean voxel-wise misclassification rate was 6.2%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. Conclusions: By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

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Osteocyte cells are the most abundant cells in human bone tissue. Due to their unique morphology and location, osteocyte cells are thought to act as regulators in the bone remodelling process, and are believed to play an important role in astronauts’ bone mass loss after long-term space missions. There is increasing evidence showing that an osteocyte’s functions are highly affected by its morphology. However, changes in an osteocyte’s morphology under an altered gravity environment are still not well documented. Several in vitro studies have been recently conducted to investigate the morphological response of osteocyte cells to the microgravity environment, where osteocyte cells were cultured on a two-dimensional flat surface for at least 24 hours before microgravity experiments. Morphology changes of osteocyte cells in microgravity were then studied by comparing the cell area to 1g control cells. However, osteocyte cells found in vivo are with a more 3D morphology, and both cell body and dendritic processes are found sensitive to mechanical loadings. A round shape osteocyte’s cells support a less stiff cytoskeleton and are more sensitive to mechanical stimulations compared with flat cellular morphology. Thus, the relative flat and spread shape of isolated osteocytes in 2D culture may greatly hamper their sensitivity to a mechanical stimulus, and the lack of knowledge on the osteocyte’s morphological characteristics in culture may lead to subjective and noncomprehensive conclusions of how altered gravity impacts on an osteocyte’s morphology. Through this work empirical models were developed to quantitatively predicate the changes of morphology in osteocyte cell lines (MLO-Y4) in culture, and the response of osteocyte cells, which are relatively round in shape, to hyper-gravity stimulation has also been investigated. The morphology changes of MLO-Y4 cells in culture were quantified by measuring cell area and three dimensionless shape features including aspect ratio, circularity and solidity by using widely accepted image analysis software (ImageJTM). MLO-Y4 cells were cultured at low density (5×103 per well) and the changes in morphology were recorded over 10 hours. Based on the data obtained from the imaging analysis, empirical models were developed using the non-linear regression method. The developed empirical models accurately predict the morphology of MLO-Y4 cells for different culture times and can, therefore, be used as a reference model for analysing MLO-Y4 cell morphology changes within various biological/mechanical studies, as necessary. The morphological response of MLO-Y4 cells with a relatively round morphology to hyper-gravity environment has been investigated using a centrifuge. After 2 hours culture, MLO-Y4 cells were exposed to 20g for 30mins. Changes in the morphology of MLO-Y4 cells are quantitatively analysed by measuring the average value of cell area and dimensionless shape factors such as aspect ratio, solidity and circularity. In this study, no significant morphology changes were detected in MLO-Y4 cells under a hyper-gravity environment (20g for 30 mins) compared with 1g control cells.

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Collisions between pedestrians and vehicles continue to be a major problem throughout the world. Pedestrians trying to cross roads and railway tracks without any caution are often highly susceptible to collisions with vehicles and trains. Continuous financial, human and other losses have prompted transport related organizations to come up with various solutions addressing this issue. However, the quest for new and significant improvements in this area is still ongoing. This work addresses this issue by building a general framework using computer vision techniques to automatically monitor pedestrian movements in such high-risk areas to enable better analysis of activity, and the creation of future alerting strategies. As a result of rapid development in the electronics and semi-conductor industry there is extensive deployment of CCTV cameras in public places to capture video footage. This footage can then be used to analyse crowd activities in those particular places. This work seeks to identify the abnormal behaviour of individuals in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM), Full-2D HMM and Spatial HMM to model the normal activities of people. The outliers of the model (i.e. those observations with insufficient likelihood) are identified as abnormal activities. Location features, flow features and optical flow textures are used as the features for the model. The proposed approaches are evaluated using the publicly available UCSD datasets, and we demonstrate improved performance using a Semi-2D Hidden Markov Model compared to other state of the art methods. Further we illustrate how our proposed methods can be applied to detect anomalous events at rail level crossings.

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Vacuum cleaners can release large concentrations of particles, both in their exhaust air and from resuspension of settled dust. However, the size, variability and microbial diversity of these emissions are unknown, despite evidence to suggest they may contribute to allergic responses and infection transmission indoors. This study aimed to evaluate bioaerosol emission from various vacuum cleaners. We sampled the air in an experimental flow tunnel where vacuum cleaners were run and their airborne emissions sampled with closed-face cassettes. Dust samples were also 35 collected from the dust bag. Total bacteria, total archaea, Penicillium/Aspergillus and total Clostridium cluster 1 were quantified with specific qPCR protocols and emission rates were calculated. Clostridium botulinum, as well as antibiotic resistance genes were detected in each sample using endpoint PCR. Bacterial diversity was also analyzed using denaturing gel electrophoresis (DGGE), image analysis and band sequencing. We demonstrated that emission of bacteria and moulds (Pen/Asp) can reach values as high as 1E05/min and that those emissions are not related to each other. The bag dust bacterial and mould content was also consistently across the vacuums we assessed, reaching up to 1E07 bacteria or moulds equivalent/g. Antibiotic resistance genes were detected in several samples. No archaea or C. botulinum were detected in any air samples. Diversity analyses showed that most bacteria are from human sources, in keeping with other recent results. These results highlight the potential capability of vacuum cleaners to disseminate appreciable quantities of moulds and human-associated bacteria indoors and their role as a source of exposure to bioaerosols.

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Cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. The rich sources of prior information in IGRT are incorporated into a hidden Markov random field model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk. The voxel labels are estimated using iterated conditional modes. The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom. The mean voxel-wise misclassification rate was 6.2\%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

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Non-periodic structural variation has been found in the high Tc cuprates, YBa2Cu3O7-x and Hg0.67Pb0.33Ba2Ca2Cu 3O8+δ, by image analysis of high resolution transmission electron microscope (HRTEM) images. We use two methods for analysis of the HRTEM images. The first method is a means for measuring the bending of lattice fringes at twin planes. The second method is a low-pass filter technique which enhances information contained by diffuse-scattered electrons and reveals what appears to be an interference effect between domains of differing lattice parameter in the top and bottom of the thin foil. We believe that these methods of image analysis could be usefully applied to the many thousands of HRTEM images that have been collected by other workers in the high temperature superconductor field. This work provides direct structural evidence for phase separation in high Tc cuprates, and gives support to recent stripes models that have been proposed to explain various angle resolved photoelectron spectroscopy and nuclear magnetic resonance data. We believe that the structural variation is a response to an opening of an electronic solubility gap where holes are not uniformly distributed in the material but are confined to metallic stripes. Optimum doping may occur as a consequence of the diffuse boundaries between stripes which arise from spinodal decomposition. Theoretical ideas about the high Tc cuprates which treat the cuprates as homogeneous may need to be modified in order to take account of this type of structural variation.

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The assessment of choroidal thickness from optical coherence tomography (OCT) images of the human choroid is an important clinical and research task, since it provides valuable information regarding the eye’s normal anatomy and physiology, and changes associated with various eye diseases and the development of refractive error. Due to the time consuming and subjective nature of manual image analysis, there is a need for the development of reliable objective automated methods of image segmentation to derive choroidal thickness measures. However, the detection of the two boundaries which delineate the choroid is a complicated and challenging task, in particular the detection of the outer choroidal boundary, due to a number of issues including: (i) the vascular ocular tissue is non-uniform and rich in non-homogeneous features, and (ii) the boundary can have a low contrast. In this paper, an automatic segmentation technique based on graph-search theory is presented to segment the inner choroidal boundary (ICB) and the outer choroidal boundary (OCB) to obtain the choroid thickness profile from OCT images. Before the segmentation, the B-scan is pre-processed to enhance the two boundaries of interest and to minimize the artifacts produced by surrounding features. The algorithm to detect the ICB is based on a simple edge filter and a directional weighted map penalty, while the algorithm to detect the OCB is based on OCT image enhancement and a dual brightness probability gradient. The method was tested on a large data set of images from a pediatric (1083 B-scans) and an adult (90 B-scans) population, which were previously manually segmented by an experienced observer. The results demonstrate the proposed method provides robust detection of the boundaries of interest and is a useful tool to extract clinical data.

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Objectives: Superficial bladder cancer (SBC) presents a difficult clinical dilemma at diagnosis as only a small subgroup of patients will subsequently develop invasive disease. Study of cancer biology has found that angiogenesis is central to growth and spread. This study examines the relationship between the angiogenic inhibitory factor Thrombospondin-1 (TSP-1) at initial presentation and subsequent progression of SBC. Methods: Using immunohistochemistry, 220 cases of SBC were examined for pattern and extent of expression of TSP-1 at initial presentation. Results: TSP-1 was detected in perivascular tissue, at the epithelial-stromal junction, in the stroma and in tumour cells and reduced perivascular TSP-1 staining at presentation was an independent predictive factor for the subsequent development of muscle invasive or metastatic disease. Conclusion: This adds further weight to the theory that TSP-1 plays a major part in the biology of bladder cancer possibly through the control of angiogenesis. © 2002 Elsevier Science B.V. All rights reserved.

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To investigate the correlation between postmenopausal osteoporosis (PMO) and the pathogenesis of periodontitis, ovariectomized rats were generated and the experimental periodontitis was induced using a silk ligature. The inflammatory factors and bone metabolic markers were measured in the serum and periodontal tissues of ovariectomized rats using an automatic chemistry analyzer, enzyme-linked immunosorbent assays, and immunohistochemistry. The bone mineral density of whole body, pelvis, and spine was analyzed using dual-energy X-ray absorptiometry and image analysis. All data were analyzed using SPSS 13.0 statistical software. It was found that ovariectomy could upregulate the expression of interleukin- (IL-)6, the receptor activator of nuclear factor-κB ligand (RANKL), and osteoprotegerin (OPG) and downregulate IL-10 expression in periodontal tissues, which resulted in progressive alveolar bone loss in experimental periodontitis. This study indicates that changes of cytokines and bone turnover markers in the periodontal tissues of ovariectomized rats contribute to the damage of periodontal tissues.

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Introduction Stretching of tissue stimulates angiogenesis but increased motion at a fracture site hinders revascularisation. In vitro studies have indicated that mechanical stimuli promote angiogenic responses in endothelial cells, but can either inhibit or enhance responses when applied directly to angiogenesis assays. We anticipated that cyclic tension applied during endothelial network assembly would increase vascular structure formation up to a certain threshold. Methods Fibroblast/HUVEC co-cultures were subjected to cyclic equibiaxial strain (1 Hz; 6 h/day; 7 days) using the FlexerCell FX-4000T system and limiting rings for simultaneous application of multiple strain magnitudes (0–13%). Cells were labelled using anti-PECAM-1, and image analysis provided measures of endothelial network length and numbers of junctions. Results Cyclic stretching had no significant effect on the total length of endothelial networks (P > 0.2) but resulted in a strain-dependent decrease in branching and localised alignments of endothelial structures, which were in turn aligned with the supporting fibroblastic construct. Conclusion The organisation of endothelial networks under cyclic strain is dominated by structural adaptation to the supporting construct. It may be that, in fracture healing, the formation and integrity of the granulation tissue and callus is ultimately critical in revascularisation and its failure under severe strain conditions.

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BACKGROUND: Burn sepsis is a leading cause of mortality and morbidity in patients with major burns. The use of topical antimicrobial agents has helped improve the survival of these patients. Silvazine (Sigma Pharmaceuticals, Melbourne, Australia) (1% silver sulphadiazine and 0.2% chlorhexidine digluconate) is used exclusively in Australasia, and there is no published study on its cytotoxicity. This study compared the relative cytotoxicity of Silvazine with 1% silver sulphadiazine (Flamazine (Smith & Nephew Healthcare, Hull, UK)) and a silver-based dressing (Acticoat (Smith & Nephew Healthcare, Hull, UK)). METHODS: Dressings were applied to the centre of culture plates that were then seeded with keratinocytes at an estimated 25% confluence. The plates were incubated for 72 h and culture medium and dressings then removed. Toluidine blue was added to stain the remaining keratinocytes. Following removal of the dye, the plates were photographed under standard conditions and these digital images were analysed using image analysis software. Data was analysed using Student's t-test. RESULTS: In the present study, Silvazine is the most cytotoxic agent. Seventy-two hour exposure to Silvazine in the present study results in almost no keratinocyte survival at all and a highly statistically significant reduction in cell survival relative to control, Acticoat and Flamazine (P<0.001, P<0.01, P<0.01, respectively). Flamazine is associated with a statistically significant reduction in cell numbers relative to control (P<0.05), but is much less cytotoxic than Silvazine (P<0.005). CONCLUSION: In this in-vitro study comparing Acticoat, Silvazine and Flamazine, Silvazine shows an increased cytotoxic effect, relative to control, Flamazine and Acticoat. An in-vivo study is required to determine whether this effect is carried into the clinical setting.

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In vivo confocal microscopy (IVCM) is an emerging technology that provides minimally invasive, high resolution, steady-state assessment of the ocular surface at the cellular level. Several challenges still remain but, at present, IVCM may be considered a promising technique for clinical diagnosis and management. This mini-review summarizes some key findings in IVCM of the ocular surface, focusing on recent and promising attempts to move “from bench to bedside”. IVCM allows prompt diagnosis, disease course follow-up, and management of potentially blinding atypical forms of infectious processes, such as acanthamoeba and fungal keratitis. This technology has improved our knowledge of corneal alterations and some of the processes that affect the visual outcome after lamellar keratoplasty and excimer keratorefractive surgery. In dry eye disease, IVCM has provided new information on the whole-ocular surface morphofunctional unit. It has also improved understanding of pathophysiologic mechanisms and helped in the assessment of prognosis and treatment. IVCM is particularly useful in the study of corneal nerves, enabling description of the morphology, density, and disease- or surgically induced alterations of nerves, particularly the subbasal nerve plexus. In glaucoma, IVCM constitutes an important aid to evaluate filtering blebs, to better understand the conjunctival wound healing process, and to assess corneal changes induced by topical antiglaucoma medications and their preservatives. IVCM has significantly enhanced our understanding of the ocular response to contact lens wear. It has provided new perspectives at a cellular level on a wide range of contact lens complications, revealing findings that were not previously possible to image in the living human eye. The final section of this mini-review provides a focus on advances in confocal microscopy imaging. These include 2D wide-field mapping, 3D reconstruction of the cornea and automated image analysis.

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Moving cell fronts are an essential feature of wound healing, development and disease. The rate at which a cell front moves is driven, in part, by the cell motility, quantified in terms of the cell diffusivity $D$, and the cell proliferation rate �$\lambda$. Scratch assays are a commonly-reported procedure used to investigate the motion of cell fronts where an initial cell monolayer is scratched and the motion of the front is monitored over a short period of time, often less than 24 hours. The simplest way of quantifying a scratch assay is to monitor the progression of the leading edge. Leading edge data is very convenient since, unlike other methods, it is nondestructive and does not require labeling, tracking or counting individual cells amongst the population. In this work we study short time leading edge data in a scratch assay using a discrete mathematical model and automated image analysis with the aim of investigating whether such data allows us to reliably identify $D$ and $\lambda$�. Using a naıve calibration approach where we simply scan the relevant region of the ($D$;$\lambda$�) parameter space, we show that there are many choices of $D$ and $\lambda$� for which our model produces indistinguishable short time leading edge data. Therefore, without due care, it is impossible to estimate $D$ and $\lambda$� from this kind of data. To address this, we present a modified approach accounting for the fact that cell motility occurs over a much shorter time scale than proliferation. Using this information we divide the duration of the experiment into two periods, and we estimate $D$ using data from the first period, while we estimate �$\lambda$ using data from the second period. We confirm the accuracy of our approach using in silico data and a new set of in vitro data, which shows that our method recovers estimates of $D$ and $\lamdba$� that are consistent with previously-reported values except that that our approach is fast, inexpensive, nondestructive and avoids the need for cell labeling and cell counting.

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During invasion and metastasis, cancer cells interact closely with the extracellular matrix molecules by attachment, degradation, and migration. We demonstrated previously the local degradation of fluorescently labeled gelatin matrix by cancer cells at invasive membrane protrusions, called invadopodia. Using the newly developed quantitative fluorescence-activated cell sorting-phagocytosis assay and image analysis of localized degradation of fluorescently labeled matrix, we document here that degradation and site- specific removal of cross-linked gelatin matrix is correlated with the extent of phagocytosis in human breast cancer cells. A higher phagocytic capacity is generally associated with increasing invasiveness, documented in other invasion and motility assays as well. Gelatin phagocytosis is time and cell density dependent, and it is mediated by the actin cytoskeleton. Most of the intracellular gelatin is routed to actively acidified vesicles, as demonstrated by the fluorescent colocalization of gelatin with acidic vesicles, indicating the intracellular degradation of the phagocytosed matrix in lysosomes. We show here that normal intracellular routing is blocked after treatment with acidification inhibitors. In addition, the need for partial proteolytic degradation of the matrix prior to phagocytosis is demonstrated by the inhibition of gelatin phagocytosis with different serine and metalloproteinase inhibitors and its stimulation by conditioned medium containing the matrix metalloproteinases MMP-2 and MMP-9. Our results demonstrate that phagocytosis of extracellular matrix is an inherent feature of breast tumor cells that correlates with and may even directly contribute to their invasive capacity. This assay is useful for screening and evaluating potential anti-invasive agents because it is fast, reproducible, and versatile.