Técnicas de correlação no delineamento de feições rodoviárias em imagens de baixa e média resolução

This paper presents a method for the sequential road feature delineation from digital images. It is based on a feedback loop between extrapolation and refinement steps of a given road centerline point, using in both steps correlation techniques. Firstly, a previously extracted road centerline point is linearly extrapolated, resulting in an approximate position. Secondly, this approximate position is corrected by comparing gray level profiles extracted perpendicularly to the extrapolation direction. This strategy is then repeated to allow the entire road centerline to be extracted or a stop point to be found. In order to initialize the extraction process, the operator needs to supply a starting point plus direction and width. Experimental results obtained from the application of the method to real image data are presented and discussed in this paper.

Estudo de métodos para classificação e localização precisa de padrões usando um sistema de luz estruturada

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Avaliação da influência da velocidade de perfuração na reabsorção óssea ao redor de implantes osseointegrados instalados por meio de cirurgia guiada sem retalho: estudo clínico, radiográfico e histológico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Determinação da qualidade da radiografia digital aplicada às soldas de gasodutos e oleodutos terrestres e marítimos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise histológica da utilização da matriz dérmica acelular e da matriz de pericárdio bovino, associados ao retalho reposicionado coronariamente, no tratamento de deiscências ósseas criadas cirurgicamente em cães

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fractal descriptors for discrimination of microscopy images of plant leaves

This study proposes the application of fractal descriptors method to the discrimination of microscopy images of plant leaves. Fractal descriptors have demonstrated to be a powerful discriminative method in image analysis, mainly for the discrimination of natural objects. In fact, these descriptors express the spatial arrangement of pixels inside the texture under different scales and such arrangements are directly related to physical properties inherent to the material depicted in the image. Here, we employ the Bouligand-Minkowski descriptors. These are obtained by the dilation of a surface mapping the gray-level texture. The classification of the microscopy images is performed by the well-known Support Vector Machine (SVM) method and we compare the success rate with other literature texture analysis methods. The proposed method achieved a correctness rate of 89%, while the second best solution, the Co-occurrence descriptors, yielded only 78%. This clear advantage of fractal descriptors demonstrates the potential of such approach in the analysis of the plant microscopy images.

Peritoneal dialysis per se is a risk factor for sclerostin-associated adynamic bone disease

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Análise da efetividade de polimerização, adaptação marginal e interna de restaurações Classe II de resinas compostas de inserção em bloco utilizando diferentes matrizes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Segmentação de texturas em imagens digitais utilizando wavelets redundantes

Pós-graduação em Matematica Aplicada e Computacional - FCT

An Analysis of Anchitherine Equids Across the Eocene–Oligocene Boundary in the White River Group of the Western Great Plains

Anchitherine horses are a subfamily of equids that are abundantly represented in the late Eocene and early Oligocene of North America. This group has been heavily studied in the past, but important questions still remain. Some studies have focused on the Eocene-Oligocene boundary and have used these equids along with other taxa to study mammalian diet and climate change through this interval. I reexamine two anchitherine genera, Mesohippus and Miohippus, from stratigraphic sequences of the White River Group in western Nebraska and southwestern South Dakota. These sequences span the Chadronian (late Eocene), Orellan (early Oligocene), and Whitneyan (early Oligocene) North American land-mammal ages. The most recent revision of these genera was done by Prothero and Shubin (1989). I review the characters used for taxonomic identification. This includes characters such as the hypostyle, the articular facet on the third metatarsal, and dental dimensions. To avoid possible biases caused by combining specimens from different stratigraphic levels, specimens were separated by location and stratigraphic level. The length and width of cheek teeth, and tooth rows were measured on 488 specimens. First molar area serves as a proxy for body mass in horses and other mammals, and can be useful for distinguishing among species. Results indicate that the characters used by Prothero and Shubin were highly variable in anchitherine horses and are not useful for distinguishing between these genera. The development of the articular facet on the third metatarsal may be a function of body size and therefore may be of no more utility than first molar area. Variability in first molar area suggests the presence of three species in the medial and late Chadronian, two species in the Orellan, and at least two species in the Whitneyan. Due to a lack of objective criteria separating Mesohippus from Miohippus, I recommend synonymy of these genera, making Mesohippus a junior subjective synonym.

EDGE-PRESERVING SPECKLE TEXTURE REMOVAL BY INTERFERENCE-BASED SPECKLE FILTERING FOLLOWED BY ANISOTROPIC DIFFUSION

Ultrasonography has an inherent noise pattern, called speckle, which is known to hamper object recognition for both humans and computers. Speckle noise is produced by the mutual interference of a set of scattered wavefronts. Depending on the phase of the wavefronts, the interference may be constructive or destructive, which results in brighter or darker pixels, respectively. We propose a filter that minimizes noise fluctuation while simultaneously preserving local gray level information. It is based on steps to attenuate the destructive and constructive interference present in ultrasound images. This filter, called interference-based speckle filter followed by anisotropic diffusion (ISFAD), was developed to remove speckle texture from B-mode ultrasound images, while preserving the edges and the gray level of the region. The ISFAD performance was compared with 10 other filters. The evaluation was based on their application to images simulated by Field II (developed by Jensen et al.) and the proposed filter presented the greatest structural similarity, 0.95. Functional improvement of the segmentation task was also measured, comparing rates of true positive, false positive and accuracy. Using three different segmentation techniques, ISFAD also presented the best accuracy rate (greater than 90% for structures with well-defined borders). (E-mail: fernando.okara@gmail.com) (C) 2012 World Federation for Ultrasound in Medicine & Biology.

Ultrasonic tissue characterization of vulnerable carotid plaque: correlation between videodensitometric method and histological examination

Abstract Background To establish the correlation between quantitative analysis based on B-mode ultrasound images of vulnerable carotid plaque and histological examination of the surgically removed plaque, on the basis of a videodensitometric digital texture characterization. Methods Twenty-five patients (18 males, mean age 67 ± 6.9 years) admitted for carotid endarterectomy for extracranial high-grade internal carotid artery stenosis (≥ 70% luminal narrowing) underwent to quantitative ultrasonic tissue characterization of carotid plaque before surgery. A computer software (Carotid Plaque Analysis Software) was developed to perform the videodensitometric analysis. The patients were divided into 2 groups according to symptomatology (group I, 15 symptomatic patients; and group II, 10 patients asymptomatic). Tissue specimens were analysed for lipid, fibromuscular tissue and calcium. Results The first order statistic parameter mean gray level was able to distinguish the groups I and II (p = 0.04). The second order parameter energy also was able to distinguish the groups (p = 0,02). A histological correlation showed a tendency of mean gray level to have progressively greater values from specimens with < 50% to >75% of fibrosis. Conclusion Videodensitometric computer analysis of scan images may be used to identify vulnerable and potentially unstable lipid-rich carotid plaques, which are less echogenic in density than stable or asymptomatic, more densely fibrotic plaques.

Morphologic micro–computed tomography analysis of mandibular premolars with three root canals

Introduction: This study aimed to describe the anatomy of mandibular premolars with type IX canal configuration by using micro–computed tomography. Methods: Mandibular premolars with radicular grooves (n = 105) were scanned, and 16 teeth with type IX configuration were selected. Number and location of canals, distances between anatomic landmarks, occurrence of apical delta, root canal fusion, and furcation canals, as well as 2-dimensional (area, perimeter, roundness, major and minor diameters) and 3-dimensional (volume, surface area, and structuremodel index) analysis were performed. Data were statistically compared by using analysis of variance and Kruskal-Wallis tests (a = 0.05). Results: Overall, specimens had 1 root with a main canal that divided into mesiobuccal, distobuccal, and lingual canals at the furcation level. Mean length of the teeth was 22.9 2.06 mm, and the configuration of the pulp chamber was mostly triangle-shaped. Mean distances from the furcation to the apex and cementoenamel junction were 9.14 2.07 and 5.59 2.19 mm, respectively. Apical delta, root canal fusion, and furcation canals were present in 4, 5, and 10 specimens, respectively. No statistical differences were found in the 2-dimensional and 3-dimensional analyses between root canals (P > .05). Conclusions: Type IX configuration of the root canal system was found in 16 of 105 mandibular premolars with radicular grooves. Most of the specimens had a triangle-shaped pulp chamber. Within this anatomic configuration, complexities of the root canal systems such as the presence of furcation canals, fusion of canals, oval-shaped canals in the apical third, small orifices at the pulp chamber level, and apical delta were also observed

Evaluation of texture features in hepatic tissue characterization from non-enhanced CT images

Aim of this paper is to evaluate the diagnostic contribution of various types of texture features in discrimination of hepatic tissue in abdominal non-enhanced Computed Tomography (CT) images. Regions of Interest (ROIs) corresponding to the classes: normal liver, cyst, hemangioma, and hepatocellular carcinoma were drawn by an experienced radiologist. For each ROI, five distinct sets of texture features are extracted using First Order Statistics (FOS), Spatial Gray Level Dependence Matrix (SGLDM), Gray Level Difference Method (GLDM), Laws' Texture Energy Measures (TEM), and Fractal Dimension Measurements (FDM). In order to evaluate the ability of the texture features to discriminate the various types of hepatic tissue, each set of texture features, or its reduced version after genetic algorithm based feature selection, was fed to a feed-forward Neural Network (NN) classifier. For each NN, the area under Receiver Operating Characteristic (ROC) curves (Az) was calculated for all one-vs-all discriminations of hepatic tissue. Additionally, the total Az for the multi-class discrimination task was estimated. The results show that features derived from FOS perform better than other texture features (total Az: 0.802+/-0.083) in the discrimination of hepatic tissue.

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.