Navegando por Autor "Oliveira, Maria Cristina Ferreira de"

Agora exibindo 1 - 6 de 6
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    Ambiente InfoVis - descrição da arquitetura e aspectos de implementação.
    (2002-11) Shimabukuro, Milton Hirokazu; Branco, Vinícius Alves Marques; Oliveira, Maria Cristina Ferreira de
    Este documento descreve a arquitetura proposta para o InfoVis, um ambiente cujo objetivo é disponibilizar, de forma integrada e acessível, diversas técnicas de visualização de informação para apoiar tarefas de análise e exploração de dados. Os diferentes componentes da arquitetura são introduzidos, bem como o mecanismo de comunicação que garante a execução integrada dos diferentes componentes. Uma versão inicial da interface de acesso é apresentada, e aspectos relacionados a plataforma de implementação são discutidos.
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    Combination of techniques to enrich visualization in dentistry.
    (2000-12) Minghim, Rosane; Soares, Igor Prata; Oliveira, Maria Cristina Ferreira de; Nonato, Luis Gustavo
    This paper reports on the implementation of two diflerent approaches for visualization of dentistry data, discussing their role in providing adequate support for training, exploration, simulation and interaction in Dentistry applications. One of the approaches is a reconstruction technique based on the Delaunay Triangulation, and the other is a Direct Volumetric Rendering and Visualization technique with texture mapping. The results are evaluated in the light of the target applications, which are teaching and training in dentistry, as well as simulation of dental procedures and illnesses. Uses for multiple-technique visualization and exploration are discussed.
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    Desenvolvimento de um sistema de visualização para neurônios artificiais.
    (2002-05) Colturato, Danielle Bentivoglio; Oliveira, Maria Cristina Ferreira de; Valerio Netto, Antonio
    Este artigo descreve uma aplicação desenvolvida em colaboração com os pesquisadores do Grupo de Visão Cibernética do IFSC-USP (Instituto de Física de São Carlos-Universidade de São Paulo) que visa apresentar um ambiente interativo para visualização de dados de neurônios gerados por esses usuários, auxiliando dessa forma, o processo de análise dos mesmos. Este sistema permite manipulação dos neurônios por meio de cortes na isosuperticie, escolha de parâmetros (cor,. tipo de técnica de visualização, valor da isosuperficie, etc.). Como ferramenta para auxiliar o desenvolvimento do sistema foi utilizada a biblioteca de classes VTK (The Visualization Toolkit).
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    Implementing and applying direct volume rendering with textures.
    (2000-12) Soares, Igor Prata; Minghim, Rosane; Oliveira, Maria Cristina Ferreira de; Nonato, Luis Gustavo
    This paper reports on the implementation of a Direct Volumetric Rendering (DVR) and Visualization techniquein the context of a general-purpose, low cost visualization software with available source code. The technique employs a texture mapping strategy to combine scalar values of volumetric data into three-dimensionalimages. Relevant implementation issues of this technique are presented, and the results are discussed in the light of a target application, namely visualization in dentistry. The technique presented here, DVRT, has demonstrated to behave better than the ray casting DVR technique for the data sets of interest, and also to produce very good results under shading.
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    Método de Hartmann-Shack: noções gerais e aspectos relevantes.
    (2002-05) Valerio Netto, Antonio; Oliveira, Maria Cristina Ferreira de
    [sem resumo]
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    Proposal to use artificial intelligence in the field of opthalmology.
    (2002-05) Valerio Netto, Antonio; Oliveira, Maria Cristina Ferreira de
    This project consists of investigating a technology to make possible the automatic mensuration of the ocular refraction errors (astigmatism, hypemietropia and myopia). For this, it intends to use recognition techniques and images analysis that will operate on images acquired recently by technique used for the information acquisition from the ocular globe, called Hartmann—Shack. The system should process an image supplied by the acquisition technique and, later on, to analyze it, extracting the necessary information for an automatic diagnosis of the possible existence of refractive errors in the examined ocular globe. The approach to be adopted uses techniques of artificial intelligence, more specifically, the use of neural networks. The huge progress in research and practical applications in that line in the last years certifies the precision and the efficiency of the same to analyze and to recognize external input data. It is believed that they can be used to identify an image from Hartrnann-Shack sensor that corresponds to an eye with anomaly, which anomaly type, as well as to quantify the magnitude anomaly. The purpose of using neural networks in the image analysis is to provide to the system with adaptability and robustness, that is, the system can respond (to measure) by understanding the data and not comparing the images as was accomplished previously. The use of intelligent software to evaluate the images also seeks to solve current problems of the difficulties that exist today for optimizing the system. Problems with small imperfections in the image acquisition or digitalization, in the preprocessing and segmentation of the images, can cause mistakes later on in the moment of the mensuration. This approach offers various possibilities in terms of academic research and ocular globe recognition. The possibility to recognize and to analyze the pertinent characteristics of the ocular globe allows to diagnose the refraction errors, and to obtain other information about the health of the ocular globe. Furthermore, a practical contribution of this approach is to suggest a new technology to measure the ocular refraction errors and the computational contribution based on analysis techniques and images recognition. Another contribution consists of the introduction of those techniques in a new field. It is possible that new application demands adaptations/new developments in the current processes, which can result in a contribution by this project for the computation area in addition to the immediate application of existent techniques. Finally, we believe the project provides a good opportunity for a closer approximation between the areas of Computer Science and Optometry.