993 resultados para Oocyte morphological classification
Resumo:
Fuzzy-reasoning theory is widely used in industrial control. Mathematical morphology is a powerful tool to perform image processing. We apply fuzzy-reasoning theory to morphology and suggest a scheme of fuzzy-reasoning morphology, including fuzzy-reasoning dilation and erosion functions. These functions retain more fine details than the corresponding conventional morphological operators with the same structuring element. An optical implementation has been developed with area-coding and thresholding methods. (C) 1997 Optical Society of America.
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Based on birefringence, a building-block stacking technique is suggested in this paper. A solid-state optical morphological processor module is thus developed, which is an integration of a beam array generator submodule, an optical connector submodule, and a Pockels readout optical modulator. It is shown that the technique is compact in construction, simple for fabrication, and insensitive to the environment.
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An ordered gray-scale erosion is suggested according to the definition of hit-miss transform. Instead of using three operations, two images, and two structuring elements, the developed operation requires only one operation and one structuring element, but with three gray-scale levels. Therefore, a union of the ordered gray-scale erosions with different structuring elements can constitute a simple image algebra to program any combined image processing function. An optical parallel ordered gray-scale erosion processor is developed based on the incoherent correlation in a single channel. Experimental results are also given for an edge detection and a pattern recognition. (C) 1998 Society of Photo-Optical Instrumentation Engineers. [S0091-3286(98)00306-7].
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In the Ukraine there are several thousand large, medium and small lakes and lake-like reservoirs, distinguished by origin, salinity, regional position, productivity and by construction a significant number of large and small water bodies, ponds and industrial reservoirs of variable designation. The problem of national systems necessitates the creation of specific schemes and classifications. Classifying into specific types of reservoir by means of suitable specifications is required for planning national measures with the objective of the rational utilisation of natural resources. It is now necessary to consider the present-day characteristics of Ukranian lakes. In the case of the Ukraine it is possible to use two approaches - genetical and ecological. This paper uses the genetical system to classify the lake-like water bodies of the Ukraine.
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Morphological observations on the two types of Pseudospora are given. The two Pseudospora whic are described are Pseudospora eudorini and Pseudospora volvocis. The systematic classification of the genus Pseudospora is discussed.
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This article describes the progress of the River Communities Project which commenced in 1977. This project aimed to develop a sensitive and practical system for river site classification using macroinvertebrates as an objective means of appraising the status of British rivers. The relationship between physical and chemical features of sites and their biological communities were examined. Sampling was undertaken on 41 British rivers. Ordination techniques were used to analyze data and the sites were classified into 16 groups using multiple discrimination analysis. The potential for using the environmental data to predict to which group a site belonged and the fauna likely to be present was investigated.
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In recent years, the performance of semi-supervised learning has been theoretically investigated. However, most of this theoretical development has focussed on binary classification problems. In this paper, we take it a step further by extending the work of Castelli and Cover [1] [2] to the multi-class paradigm. Particularly, we consider the key problem in semi-supervised learning of classifying an unseen instance x into one of K different classes, using a training dataset sampled from a mixture density distribution and composed of l labelled records and u unlabelled examples. Even under the assumption of identifiability of the mixture and having infinite unlabelled examples, labelled records are needed to determine the K decision regions. Therefore, in this paper, we first investigate the minimum number of labelled examples needed to accomplish that task. Then, we propose an optimal multi-class learning algorithm which is a generalisation of the optimal procedure proposed in the literature for binary problems. Finally, we make use of this generalisation to study the probability of error when the binary class constraint is relaxed.
Resumo:
As hepatites crônicas por vírus são as mais frequentes, destacando-se os vírus das hepatites B (VHB) e C (VHC). O estudo anatomopatológico da biópsia hepática é considerado o padrão ouro para avaliar com precisão a distorção arquitetural e o grau de fibrose do parênquima do fígado, importantes fatores prognósticos para os pacientes portadores de hepatites crônicas virais. Na avaliação histopatológica atual, em adição aos relatos subjetivos das alterações histológicas, escores semiquantitativos que correlacionam achados morfológicos com graus numéricos são usados, tais como os reconhecidos escores de Ishak e METAVIR. Entretanto, em todos estes sistemas há a desvantagem da subjetividade do examinador e da incorporação de alterações categóricas, sem referências às mudanças quantitativas do colágeno hepático. Técnicas de análise de imagens digitais (AID) que fornecem quantificação objetiva dos graus de fibrose em amostras histológicas têm sido desenvolvidas. Todavia, o alto custo e dificuldade ao acesso das tecnologias descritas restringem seu uso a poucos centros especializados. Este estudo visa o desenvolvimento de uma técnica de custo acessível para a análise de imagens digitais da fibrose hepática em hepatites crônicas virais. Foram estudadas 304 biópsias de pacientes com hepatite crônica por vírus B e C, obtidas através de agulhas Menghini. Todas as amostras tinham pelo menos 15 mm de comprimento ou cinco espaços-porta completos e foram coradas pelo método Tricrômico de Masson. O estadiamento foi feito por um único hepatopatologista experiente, sem o conhecimento dos dados clínicos dos pacientes. Os escores de Ishak e METAVIR foram aplicados. As imagens microscópicas foram digitalizadas. Os índices de fibrose foram determinados de forma automatizada, em técnica desenvolvida no programa Adobe Photoshop. Para o escore de Ishak, observamos os seguintes índices de Fibrose (IF) médios: 0,8% 0,0 (estágio 0), 2.4% 0,6 (estágio 1), 4,7% 1,6 (estágio 2), 7,4% 1,4 (estágio 3), 14,9% 3,7 (estágio 4), 23,4% 2,9 (estágio 5) e 34,5% 1,5 (estágio 6). Para a classificação METAVIR: 0,8% 0,1 (estágio F0), 3,8% 1,8 (estágio F1), 7,4% 1,4 (estágio F2), 20,4% 5,2 (estágio F3) e 34,5% 1,5 (estágio F4). Observamos uma excelente correlação entre os índices de fibrose da AID e os escores de Ishak (r=0,94; p<0,001) e METAVIR (r=0,92; p<0,001). Em relação à indicação de tratamento antiviral, foi observado IF médio de 16,4%. Em relação ao diagnóstico de cirrose, foi observado IF médio de 26,9%, para o escore de Ishak, e 34,5% para a classificação METAVIR. A reprodutibilidade intra-observador foi excelente. Este novo método de análise de imagens digitais para a quantificação de fibrose hepática tem custo acessível e foi desenvolvido com tecnologia que está disponível em todo o mundo, permitindo identificar com precisão todos os estágios de fibrose, com excelente reprodutibilidade intra-observador.