993 resultados para retina image


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It has been proposed that body image disturbance is a form of cognitive bias wherein schemas for self-relevant information guide the selective processing of appearancerelated information in the environment. This threatening information receives disproportionately more attention and memory, as measured by an Emotional Stroop and incidental recall task. The aim of this thesis was to expand the literature on cognitive processing biases in non-clinical males and females by incorporating a number of significant methodological refinements. To achieve this aim, three phases of research were conducted. The initial two phases of research provided preliminary data to inform the development of the main study. Phase One was a qualitative exploration of body image concerns amongst males and females recruited through the general community and from a university. Seventeen participants (eight male; nine female) provided information on their body image and what factors they saw as positively and negatively impacting on their self evaluations. The importance of self esteem, mood, health and fitness, and recognition of the social ideal were identified as key themes. These themes were incorporated as psycho-social measures and Stroop word stimuli in subsequent phases of the research. Phase Two involved the selection and testing of stimuli to be used in the Emotional Stroop task. Six experimental categories of words were developed that reflected a broad range of health and body image concerns for males and females. These categories were high and low calorie food words, positive and negative appearance words, negative emotion words, and physical activity words. Phase Three addressed the central aim of the project by examining cognitive biases for body image information in empirically defined sub-groups. A National sample of males (N = 55) and females (N = 144), recruited from the general community and universities, completed an Emotional Stroop task, incidental memory test, and a collection of psycho-social questionnaires. Sub-groups of body image disturbance were sought using a cluster analysis, which identified three sub-groups in males (Normal, Dissatisfied, and Athletic) and four sub-groups in females (Normal, Health Conscious, Dissatisfied, and Symptomatic). No differences were noted between the groups in selective attention, although time taken to colour name the words was associated with some of the psycho-social variables. Memory biases found across the whole sample for negative emotion, low calorie food, and negative appearance words were interpreted as reflecting the current focus on health and stigma against being unattractive. Collectively these results have expanded our understanding of processing biases in the general community by demonstrating that the processing biases are found within non-clinical samples and that not all processing biases are associated with negative functionality

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Summary Generalized Procrustes analysis and thin plate splines were employed to create an average 3D shape template of the proximal femur that was warped to the size and shape of a single 2D radiographic image of a subject. Mean absolute depth errors are comparable with previous approaches utilising multiple 2D input projections. Introduction Several approaches have been adopted to derive volumetric density (g cm-3) from a conventional 2D representation of areal bone mineral density (BMD, g cm-2). Such approaches have generally aimed at deriving an average depth across the areal projection rather than creating a formal 3D shape of the bone. Methods Generalized Procrustes analysis and thin plate splines were employed to create an average 3D shape template of the proximal femur that was subsequently warped to suit the size and shape of a single 2D radiographic image of a subject. CT scans of excised human femora, 18 and 24 scanned at pixel resolutions of 1.08 mm and 0.674 mm, respectively, were equally split into training (created 3D shape template) and test cohorts. Results The mean absolute depth errors of 3.4 mm and 1.73 mm, respectively, for the two CT pixel sizes are comparable with previous approaches based upon multiple 2D input projections. Conclusions This technique has the potential to derive volumetric density from BMD and to facilitate 3D finite element analysis for prediction of the mechanical integrity of the proximal femur. It may further be applied to other anatomical bone sites such as the distal radius and lumbar spine.

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To date, automatic recognition of semantic information such as salient objects and mid-level concepts from images is a challenging task. Since real-world objects tend to exist in a context within their environment, the computer vision researchers have increasingly incorporated contextual information for improving object recognition. In this paper, we present a method to build a visual contextual ontology from salient objects descriptions for image annotation. The ontologies include not only partOf/kindOf relations, but also spatial and co-occurrence relations. A two-step image annotation algorithm is also proposed based on ontology relations and probabilistic inference. Different from most of the existing work, we specially exploit how to combine representation of ontology, contextual knowledge and probabilistic inference. The experiments show that image annotation results are improved in the LabelMe dataset.

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Retinal image properties such as contrast and spatial frequency play important roles in the development of normal vision. For example, visual environments comprised solely of low contrast and/or low spatial frequencies induce myopia. The visual image is processed by the retina and it then locally controls eye growth. In terms of the retinal neurotransmitters that link visual stimuli to eye growth, there is strong evidence to suggest involvement of the retinal dopamine (DA) system. For example, effectively increasing retinal DA levels by using DA agonists can suppress the development of form-deprivation myopia (FDM). However, whether visual feedback controls eye growth by modulating retinal DA release, and/or some other factors, is still being elucidated. This thesis is chiefly concerned with the relationship between the dopaminergic system and retinal image properties in eye growth control. More specifically, whether the amount of retinal DA release reduces as the complexity of the image degrades was determined. For example, we investigated whether the level of retinal DA release decreased as image contrast decreased. In addition, the effects of spatial frequency, spatial energy distribution slope, and spatial phase on retinal DA release and eye growth were examined. When chicks were 8-days-old, a cone-lens imaging system was applied monocularly (+30 D, 3.3 cm cone). A short-term treatment period (6 hr) and a longer-term treatment period (4.5 days) were used. The short-term treatment tests for the acute reduction in DA release by the visual stimulus, as is seen with diffusers and lenses, whereas the 4.5 day point tests for reduction in DA release after more prolonged exposure to the visual stimulus. In the contrast study, 1.35 cyc/deg square wave grating targets of 95%, 67%, 45%, 12% or 4.2% contrast were used. Blank (0% contrast) targets were included for comparison. In the spatial frequency study, both sine and square wave grating targets with either 0.017 cyc/deg and 0.13 cyc/deg fundamental spatial frequencies and 95% contrast were used. In the spectral slope study, 30% root-mean-squared (RMS) contrast fractal noise targets with spectral fall-off of 1/f0.5, 1/f and 1/f2 were used. In the spatial alignment study, a structured Maltese cross (MX) target, a structured circular patterned (C) target and the scrambled versions of these two targets (SMX and SC) were used. Each treatment group comprised 6 chicks for ocular biometry (refraction and ocular dimension measurement) and 4 for analysis of retinal DA release. Vitreal dihydroxyphenylacetic acid (DOPAC) was analysed through ion-paired reversed phase high performance liquid chromatography with electrochemical detection (HPLC-ED), as a measure of retinal DA release. For the comparison between retinal DA release and eye growth, large reductions in retinal DA release possibly due to the decreased light level inside the cone-lens imaging system were observed across all treated eyes while only those exposed to low contrast, low spatial frequency sine wave grating, 1/f2, C and SC targets had myopic shifts in refraction. Amongst these treatment groups, no acute effect was observed and longer-term effects were only found in the low contrast and 1/f2 groups. These findings suggest that retinal DA release does not causally link visual stimuli properties to eye growth, and these target induced changes in refractive development are not dependent on the level of retinal DA release. Retinal dopaminergic cells might be affected indirectly via other retinal cells that immediately respond to changes in the image contrast of the retinal image.

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Precise, up-to-date and increasingly detailed road maps are crucial for various advanced road applications, such as lane-level vehicle navigation, and advanced driver assistant systems. With the very high resolution (VHR) imagery from digital airborne sources, it will greatly facilitate the data acquisition, data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lane information from aerial images with employment of the object-oriented image analysis method. Our proposed algorithm starts with constructing the DSM and true orthophotos from the stereo images. The road lane details are detected using an object-oriented rule based image classification approach. Due to the affection of other objects with similar spectral and geometrical attributes, the extracted road lanes are filtered with the road surface obtained by a progressive two-class decision classifier. The generated road network is evaluated using the datasets provided by Queensland department of Main Roads. The evaluation shows completeness values that range between 76% and 98% and correctness values that range between 82% and 97%.

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Background: Diagnosis of epithelial ovarian cancer (EOC) in young women has major implications including those to their reproductive potential. We evaluated depression, anxiety and body image in patients with stage I EOC treated with fertility sparing surgery (FSS) or radical surgery (RS). We also investigated fertility outcomes after FSS.----- Methods: A retrospective study was undertaken in which 62 patients completed questionnaires related to anxiety, depression, body image and fertility outcomes. Additional information on adjuvant therapy after FSS and RS and demographic details were abstracted from medical records. Both bi and multivariate regression models were used to assess the relationship between demographic, clinical and pathological results and scores for anxiety, depression and body image.----- Results: Thirty-nine patients underwent RS and the rest, FSS. The percentage of patients reporting elevated anxiety and depression (subscores ≥ 11) were 27 % and 5% respectively. The median (inter quartile range) score for body image scale (BIS) was 6 (3-15). None of the demographic or clinical factors examined showed significant association with anxiety and BIS with the exception of ‘time since diagnosis’. For depression, post-menopausal status was the only independent predictor. Among those 23 patients treated by FSS, 14 patients tried to conceive (7 successful), resulting in 7 live births, one termination of pregnancy and one miscarriage.----- Conclusion: This study shows that psychological issues are common in women treated for stage I EOC. Reproduction after FSS is feasible and lead to the birth of healthy babies in about half of patients who wished to have another child. Further prospective studies with standardised instruments are required.

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We describe the design and evaluation of a platform for networks of cameras in low-bandwidth, low-power sensor networks. In our work to date we have investigated two different DSP hardware/software platforms for undertaking the tasks of compression and object detection and tracking. We compare the relative merits of each of the hardware and software platforms in terms of both performance and energy consumption. Finally we discuss what we believe are the ongoing research questions for image processing in WSNs.