23 resultados para Medical Image Database

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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Medical images are private to doctor and patient. Digital medical images should be protected against unauthorized viewers. One way to protect digital medical images is using cryptography to encrypt the images. This paper proposes a method for encrypting medical images with a traditional symmetric cryptosystem. We use biometrics to protect the cryptographic key. Both encrypted image and cryptographic key can be transmitted over public networks with security and only the person that owns the biometrics information used in key protection can decrypt the medical image. © Springer Science+Business Media B.V. 2008.

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This paper presents the prototype of a low-cost terrestrial mobile mapping system (MMS) composed of a van, two digital video cameras, two GPS receivers, a notebook computer, and a sound frame synchronisation system. The imaging sensors are mounted as a stereo video camera on top of the vehicle together with the GPS antennae. The GPS receivers and the notebook computer are configured to record data referred to the vehicle position at a planned time interval. This position is subsequently transferred to the road images. This set of equipment and methods provide the opportunity to merge distinct techniques to make topographic maps and also to build georeferenced road image databases. Both vector maps and raster image databases, when integrated appropriately, can give spatial researchers and engineers a new technique whose application may realise better planning and analysis related to the road environment. The experimental results proved that the MMS developed at the São Paulo State University is an effective approach to inspecting road pavements, to map road marks and traffic signs, electric power poles, telephone booths, drain pipes, and many other applications important to people's safety and welfare. A small number of wad images have already been captured by the prototype as a consequence of its application in distinct projects. An efficient organisation of those images and the prompt access to them justify the need for building a georeferenced image database. By expanding it, both at the hardware and software levels, it is possible for engineers to analyse the entire road environment on their office computers.

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The pathogens manifestation in plantations are the largest cause of damage in several cultivars, which may cause increase of prices and loss of crop quality. This paper presents a method for automatic classification of cotton diseases through feature extraction of leaf symptoms from digital images. Wavelet transform energy has been used for feature extraction while Support Vector Machine has been used for classification. Five situations have been diagnosed, namely: Healthy crop, Ramularia disease, Bacterial Blight, Ascochyta Blight, and unspecified disease. © 2012 Taylor & Francis Group.

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Nowadays, systems based on biométrie techniques have a wide acceptance in many different areas, due to their levels of safety and accuracy. A biometrie technique that is gaining prominence is the identification of individuals through iris recognition. However, to be proficiently used these systems must process their recognition task as fast as possible. The goal of this work has been the development of an iris recognition method to produce results rapidly, yet without losing the recognition accuracy. The experimental results show that the method is quite promising. © 2012 Taylor & Francis Group.

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Duplex and superduplex stainless steels are class of materials of a high importance for engineering purposes, since they have good mechanical properties combination and also are very resistant to corrosion. It is known as well that the chemical composition of such steels is very important to maintain some desired properties. In the past years, some works have reported that γ 2 precipitation improves the toughness of such steels, and its quantification may reveals some important information about steel quality. Thus, we propose in this work the automatic segmentation of γ 2 precipitation using two pattern recognition techniques: Optimum-Path Forest (OPF) and a Bayesian classifier. To the best of our knowledge, this if the first time that machine learning techniques are applied into this area. The experimental results showed that both techniques achieved similar and good recognition rates. © 2012 Taylor & Francis Group.

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

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Pós-graduação em Ciências Cartográficas - FCT

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Pós-graduação em Ciências Cartográficas - FCT

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Pós-graduação em Ciência da Computação - IBILCE

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Hepatocellular carcinoma (HCC) is a primary tumor of the liver. After local therapies, the tumor evaluation is based on the mRECIST criteria, which involves the measurement of the maximum diameter of the viable lesion. This paper describes a computed methodology to measure through the contrasted area of the lesions the maximum diameter of the tumor by a computational algorithm 63 computed tomography (CT) slices from 23 patients were assessed. Non-contrasted liver and HCC typical nodules were evaluated, and a virtual phantom was developed for this purpose. Optimization of the algorithm detection and quantification was made using the virtual phantom. After that, we compared the algorithm findings of maximum diameter of the target lesions against radiologist measures. Computed results of the maximum diameter are in good agreement with the results obtained by radiologist evaluation, indicating that the algorithm was able to detect properly the tumor limits A comparison of the estimated maximum diameter by radiologist versus the algorithm revealed differences on the order of 0.25 cm for large-sized tumors (diameter > 5 cm), whereas agreement lesser than 1.0cm was found for small-sized tumors. Differences between algorithm and radiologist measures were accurate for small-sized tumors with a trend to a small increase for tumors greater than 5 cm. Therefore, traditional methods for measuring lesion diameter should be complemented with non-subjective measurement methods, which would allow a more correct evaluation of the contrast-enhanced areas of HCC according to the mRECIST criteria.

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The SPECT (Single Photon Emission Computed Tomography) systems are part of a medical image acquisition technology which has been outstanding, because the resultant images are functional images complementary to those that give anatomic information, such as X-Ray CT, presenting a high diagnostic value. These equipments acquire, in a non-invasive way, images from the interior of the human body through tomographic mapping of radioactive material administered to the patient. The SPECT systems are based on the Gamma Camera detection system, and one of them being set on a rotational gantry is enough to obtain the necessary data for a tomographic image. The images obtained from the SPECT system consist in a group of flat images that describe the radioactive distribution on the patient. The trans-axial cuts are obtained from the tomographic reconstruction techniques. There are analytic and iterative methods to obtain the tomographic reconstruction. The analytic methods are based on the Fourier Cut Theorem (FCT), while the iterative methods search for numeric solutions to solve the equations from the projections. Within the analytic methods, the filtered backprojection (FBP) method maybe is the simplest of all the tomographic reconstruction techniques. This paper's goal is to present the operation of the SPECT system, the Gamma Camera detection system, some tomographic reconstruction techniques and the requisites for the implementation of this system in a Nuclear Medicine service

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Cancer is the second main cause of death in Brazil, and according to statistics disclosed by INCA - National Cancer Institute 466,730 new cases of the disease are forecast for 2008. The storage and analysis of tumour tissues of various types and patients' clinical data, genetic profiles, characteristics of diseases and epidemiological data may provide more precise diagnoses, providing more effective treatments with higher chances for the cure of cancer. In this paper we present a Web system with a client-server architecture, which manages a relational database containing all information relating to the tumour tissue and their location in freezers, patients, medical forms, physicians, users, and others. Furthermore, it is also discussed the software engineering used to developing the system.