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.

Building roof contour extraction from LiDAR data

This paper proposes a method for the automatic extraction of building roof contours from a LiDAR-derived digital surface model (DSM). The method is based on two steps. First, to detect aboveground objects (buildings, trees, etc.), the DSM is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. Preliminary results have shown that the proposed methodology works properly.

Zinc and lead content and availability in Brazilian soil contaminated with residue of a secondary smelting lead recycling plant

The sequential extraction procedure of Zinc and lead performed in a Brazilian soil showed that it presents high pollution potential once over 90% of total lead is present in fractions where the metals can be easily mobilized. The fraction contents are as follow: F1 = 174 and 15 mg kg-1; F2 = 3155 and 9.7 mg kg -1; F3 = 99 and 1.6 mg kg -1; Residual fraction = 38 and 5.5 mg kg -1 for lead and zinc, respectively. The comparison with non contaminated soil only Pb 2+ concentration is above its intervention reference concentration, 900 mg kg -1.

Tocopherol content and fatty acid profile in soybean oil supplemented with salvia extract (Salvia officinalis L.) during heating

This paper aimed to assess the tocopherol content and evaluate the fatty acid profile in soybean oil supplemented with salvia extract during heating, so as to verify the isolated and synergistic effect of natural and synthetic antioxidants. In order to obtain the extract, the lyophilized and crushed salvia was subjected to extraction by ethyl alcohol for 30 min, with a 1:20 salvia:ethyl alcohol ratio, under continuous agitation. Afterwards, the mixture was filtered and the supernatant was subjected to the rotary evaporator at 40 °C. Later the control treatments, ES (3000 mg kg-1 salvia extract), TBHQ (50 mg kg-1), and mixture (ES+50 mg kg-1 TBHQ) were prepared and subjected to 180 °C for 20 h. Samples were taken in time intervals 0, 10, and 20 h and analysed in terms of tocopherol content and fatty acid profile. Regarding the tocopherol and fatty acid profile analysis, it was found that the extract proved efficient in oil protection, when added isolated to soybean oil subjected to thermo oxidation. According to the results, salvia extract is a viable alternative that might be applied in industrialized processing of oils as natural antioxidant.

Automatic microstructural characterization and classification using artificial intelligence techniques on ultrasound signals

Secondary phases such as Laves and carbides are formed during the final solidification stages of nickel based superalloy coatings deposited during the gas tungsten arc welding cold wire process. However, when aged at high temperatures, other phases can precipitate in the microstructure, like the γ″ and δ phases. This work presents a new application and evaluation of artificial intelligent techniques to classify (the background echo and backscattered) ultrasound signals in order to characterize the microstructure of a Ni-based alloy thermally aged at 650 and 950 °C for 10, 100 and 200 h. The background echo and backscattered ultrasound signals were acquired using transducers with frequencies of 4 and 5 MHz. Thus with the use of features extraction techniques, i.e.; detrended fluctuation analysis and the Hurst method, the accuracy and speed in the classification of the secondary phases from ultrasound signals could be studied. The classifiers under study were the recent optimum-path forest (OPF) and the more traditional support vector machines and Bayesian. The experimental results revealed that the OPF classifier was the fastest and most reliable. In addition, the OPF classifier revealed to be a valid and adequate tool for microstructure characterization through ultrasound signals classification due to its speed, sensitivity, accuracy and reliability. © 2013 Elsevier B.V. All rights reserved.

Análise de domínio para avaliação de tesauros: uma experiência com a cadeia produtiva do calçado no Brasil

Pós-graduação em Ciência da Informação - FFC

Evaluation of solvent effect on the extraction of phenolic compounds and antioxidant capacities from the berries: application of principal component analysis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

High precision and selectivity for quantitation of enrofloxacin and ciprofloxacin in five chicken tissues using solid phase extraction and ESI LC-MS/MS for application in monitoring residues

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

Development of a new clean methodology with ultrasound-assisted extraction for analysis of sodium in pet foods

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Classification of intact açai (Euterpe oleracea Mart.) and jucara (Euterpe edulis Mart) fruits based on dry matter content by means of near infrared spectroscopy

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

Improving DNA extraction quality by the salting-out method to prepare blood samples for real-time PCR.

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