236 resultados para Arterial segmentation


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The turtle Trachemys scripta elegans popularly known as American tiger water are native regions winged Florida and Mississippi, in the United States. We used twenty (20) turtles (Trachemys scripta elegans), adult males and females, which were euthanized under Resolution 714 of June 20, 2002 the Federal Council of Veterinary Medicine (CFMV). After euthanasia were identified aortas right and left to the injection of Neoprene latex 450, stained with specific pigment. To obtain the vinyl mold aorta was injected through the right and left vinyl acetate, followed by corrosion in sulfuric acid. It was observed that the pancreas is closely related to the liver, gizzard, gall bladder, and duodenum. His face cranial this distal region of the pylorus, while its caudal along the cranial region of the duodenum. Anatomically, the pancreas is an elongated body structure featuring a lightly lobed. As to the pancreas arterial vasculature is flushed in its transverse plane of two arteries arising from the celiac artery, and each antimere two pancreaticoduodenal artery in the cranial region, close to the pylorus by the pancreaticoduodenal artery flow in the caudal portion along the duodenum.

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This paper presents a novel segmentation method for cuboidal cell nuclei in images of prostate tissue stained with hematoxylin and eosin. The proposed method allows segmenting normal, hyperplastic and cancerous prostate images in three steps: pre-processing, segmentation of cuboidal cell nuclei and post-processing. The pre-processing step consists of applying contrast stretching to the red (R) channel to highlight the contrast of cuboidal cell nuclei. The aim of the second step is to apply global thresholding based on minimum cross entropy to generate a binary image with candidate regions for cuboidal cell nuclei. In the post-processing step, false positives are removed using the connected component method. The proposed segmentation method was applied to an image bank with 105 samples and measures of sensitivity, specificity and accuracy were compared with those provided by other segmentation approaches available in the specialized literature. The results are promising and demonstrate that the proposed method allows the segmentation of cuboidal cell nuclei with a mean accuracy of 97%. © 2013 Elsevier Ltd. All rights reserved.

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Human intestinal parasites constitute a problem in most tropical countries, causing death or physical and mental disorders. Their diagnosis usually relies on the visual analysis of microscopy images, with error rates that may range from moderate to high. The problem has been addressed via computational image analysis, but only for a few species and images free of fecal impurities. In routine, fecal impurities are a real challenge for automatic image analysis. We have circumvented this problem by a method that can segment and classify, from bright field microscopy images with fecal impurities, the 15 most common species of protozoan cysts, helminth eggs, and larvae in Brazil. Our approach exploits ellipse matching and image foresting transform for image segmentation, multiple object descriptors and their optimum combination by genetic programming for object representation, and the optimum-path forest classifier for object recognition. The results indicate that our method is a promising approach toward the fully automation of the enteroparasitosis diagnosis. © 2012 IEEE.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Engenharia Mecânica - FEIS