Comparative analysis of two techniques for detection and segmentation of moving bodies

This paper makes a comparative analysis of results produced by the application of two techniques for the detection and segmentation of bodies in motion captured in images sequence, namely: 1) technique based on the temporal average of the values of each pixel recorded in N consecutive image frames and, 2) technique based on historical values associated with pixels recorded in different frames of an image sequence.

IFTrace: Video segmentation of deformable objects using the Image Foresting Transform

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

Radiographic measurement of tibial joint angles in sheep

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Clinical and MRI investigation of temporomandibular joint in major depressed patients

Objective: The aim of the present study was to describe the clinical and MRI findings of the temporomandibular joint (TMJ) in patients with major depressive disorders (MDDs) of the non-psychotic type.Methods: 40 patients (80 TMJs) who were diagnosed as having MDDs were selected for this study. The clinical examination of the TMJs was conducted according to the research diagnostic criteria and temporomandibular disorders (TMDs). The MRIs were obtained bilaterally in each patient with axial, parasagittal and paracoronal sections within a real-time dynamic sequence. Two trained oral radiologists assessed all images. For statistical analyses, Fisher's exact test and chi(2) test were applied (alpha = 0.05).Results: Migraine was reported in 52.5% of subjects. Considering disc position, statistically significant differences between opening patterns with and without alteration (p = 0.00) and between present and absent joint noises (p = 0.00) were found. Regarding muscular pain, patients with and without abnormalities in disc function and patients with and without abnormalities in disc position were not statistically significant (p = 0.42 and p = 0.40, respectively). Significant differences between mandibular pathway with and without abnormalities (p=0.00) and between present and absent joint noises (p=0.00) were observed.Conclusion: Based on the preliminary results observed by clinical and MRI examination of the TMJ, no direct relationship could be determined between MDDs and TMDs. Dentomaxillofacial Radiology (2012) 41, 316-322. doi: 10.1259/dmfr/27328352

Anatomicosurgical arterial segmentation of the cat lungs (Felis catus domesticus, L., 1758)

O objetivo desta pesquisa foi estabelecer os segmentos anátomo-cirúrgicos arteriais, através da lobação e ramificação intralobar arterial, em pulmões de gato. Após a dissecção de vinte pulmões, notou-se que a artéria pulmonar direita geralmente emite um ramo para o lobo cranial e um ramo para o lobo médio, sendo originados juntos em um tronco. Um grande ramo irriga o lobo caudal na maioria dos casos. Dois ramos com origem comum no ramo arterial do lobo caudal irrigam o lobo acessório. A artéria pulmonar esquerda origina um tronco que, na maioria dos casos, emite um ramo para a porção cranial e um ramo para a porção caudal do lobo cranial esquerdo. Pode-se concluir que o pulmão direito é formado por quatro e o esquerdo por dois lobos, ocorrendo variações na ramificação arterial pulmonar.

Room-temperature photoluminescence of BaTiO3: Joint experimental and theoretical study

Strong photoluminescent emission has been measured at room temperature for noncrystalline BaT'O-3 (BT) perovskite powders. A joint experimental and theoretical study has been carried out to rationalize this phenomenon. From the experimental side, BT powder samples have been synthesized following a soft chemical processing, their crystal structure has been confirmed by x-ray data and the corresponding photoluminescence (PL) properties have been measured. Only the structurally disordered samples present PL at room temperature. From the theoretical side, first-principles quantum-mechanical techniques, based on density-functional theory at the B3LYP level, have been employed to study the electronic structure of crystalline (BT-c) and asymmetric (BT-a) models. Theoretical and experimental results are found to be consistent and their confrontation leads to an interpretation of the PL apparition at room temperature in the structurally disordered powders.

Evaluation of temporomandibular joint noise in partially edentulous patients.

In order to evaluate the presence of TMD (temporomandibular disorder), dissatisfaction related to the use of removable partial dentures (RPD) and the effect of the treatment on temporomandibular joint noises, 13 female patients with Kennedy class I and II mandibular arch were selected. Another 13 young, asymptomatic, dentate patients, also female, were used as reference. After four years, 38.4% were found to have a moderate or severe degree of TMD. Over the four years, the degree of TMD increased in 46.15% of the patients, was not affected in 20.07%, while in 15.38% it decreased or the patients remained free from signs and symptoms. About 30% of the patients at the second year and 46% after the fourth year, had complaints regarding retention and stability. It was concluded that there is no relationship between TMD and the condition of partially edentulous Kennedy class I and II, but patient dissatisfaction increased after the second year and temporomandibular joint noise was reduced significantly with the replacement of the teeth.

Fast automatic microstructural segmentation of ferrous alloy samples using optimum-path forest

In this work we propose a novel automatic cast iron segmentation approach based on the Optimum-Path Forest classifier (OPF). Microscopic images from nodular, gray and malleable cast irons are segmented using OPF, and Support Vector Machines (SVM) with Radial Basis Function and SVM without kernel mapping. Results show accurate and fast segmented images, in which OPF outperformed SVMs. Our work is the first into applying OPF for automatic cast iron segmentation. © 2010 Springer-Verlag.

Automatic segmentation of digital images applied in cardiac medical images

The digital image processing has been applied in several areas, especially where it is necessary use tools for feature extraction and to get patterns of the studied images. In an initial stage, the segmentation is used to separate the image in parts that represents a interest object, that may be used in a specific study. There are several methods that intends to perform such task, but is difficult to find a method that can easily adapt to different type of images, that often are very complex or specific. To resolve this problem, this project aims to presents a adaptable segmentation method, that can be applied to different type of images, providing an better segmentation. The proposed method is based in a model of automatic multilevel thresholding and considers techniques of group histogram quantization, analysis of the histogram slope percentage and calculation of maximum entropy to define the threshold. The technique was applied to segment the cell core and potential rejection of tissue in myocardial images of biopsies from cardiac transplant. The results are significant in comparison with those provided by one of the best known segmentation methods available in the literature. © 2010 IEEE.

Automatic segmentation of the secondary austenite-phase island precipitates in a superduplex stainless steel weld metal

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.

Automatic segmentation of latent fingerprints

Latent fingerprints are routinely found at crime scenes due to the inadvertent contact of the criminals' finger tips with various objects. As such, they have been used as crucial evidence for identifying and convicting criminals by law enforcement agencies. However, compared to plain and rolled prints, latent fingerprints usually have poor quality of ridge impressions with small fingerprint area, and contain large overlap between the foreground area (friction ridge pattern) and structured or random noise in the background. Accordingly, latent fingerprint segmentation is a difficult problem. In this paper, we propose a latent fingerprint segmentation algorithm whose goal is to separate the fingerprint region (region of interest) from background. Our algorithm utilizes both ridge orientation and frequency features. The orientation tensor is used to obtain the symmetric patterns of fingerprint ridge orientation, and local Fourier analysis method is used to estimate the local ridge frequency of the latent fingerprint. Candidate fingerprint (foreground) regions are obtained for each feature type; an intersection of regions from orientation and frequency features localizes the true latent fingerprint regions. To verify the viability of the proposed segmentation algorithm, we evaluated the segmentation results in two aspects: a comparison with the ground truth foreground and matching performance based on segmented region. © 2012 IEEE.

An automatic method for segmentation of fission tracks in epidote crystal photomicrographs

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

Segmentation of Scanning Electron Microscopy Images From Natural Rubber Samples With Gold Nanoparticles Using Starlet Wavelets

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

Algorithms for automatic segmentation of bovine embryos produced

In vitro production has been employed in bovine embryos and quantification of lipids is fundamental to understand the metabolism of these embryos. This paper presents a unsupervised segmentation method for histological images of bovine embryos. In this method, the anisotropic filter was used in the differents RGB components. After pre-processing step, the thresholding technique based on maximum entropy was applied to separate lipid droplets in the histological slides in different stages: early cleavage, morula and blastocyst. In the postprocessing step, false positives are removed using the connected components technique that identify regions with excess of dye near pellucid zone. The proposed segmentation method was applied in 30 histological images of bovine embryos. Experiments were performed with the images and statistical measures of sensitivity, specificity and accuracy were calculated based on reference images (gold standard). The value of accuracy of the proposed method was 96% with standard deviation of 3%.

Segmentation of Cell Nuclei Regions in Epithelium of Prostate Glands

This paper proposes a method for segmentation of cell nuclei regions in epithelium of prostate glands. This structure provides information to diagnosis and prognosis of prostate cancer. In the initial step, the contrast stretching technique was applied in image in order to improve the contrast between regions of interest and other regions. After, the global thresholding technique was applied and the value of threshold was defined empirically. Finally, the false positive regions were removed using the connected components technique. The performance of the proposed method was compared with the Otsu technique and statistical measures of accuracy were calculated based on reference images (gold standard). The result of the mean value of accuracy of proposed method was 93% ± 0.07.