Cytoplasmic and nuclear morphometric parameters in cytologic preparations of canine cutaneous mast cell tumors

Thirty fine-needle biopsy (FNB) samples from 28 dogs subjected to surgical resection of cutaneous mast cell tumors (MCTs) were stained with Giemsa. At least 100 neoplastic cells from each cytology slide were evaluated by morphometric analysis. The parameters were: area, perimeter of the cell, cytoplasm, nucleus and circumference factor. MCTs of grade III had a mean cellular area of 231.70 μm2 ± 57.1, and grade II had a mean of 252.30 μm2 ± 55.0. Cellular perimeter was 61.20 ± 7.1 in grade II and 59.1 ± 8.6 in grade III. Cellular parameters were not statistically different between grades (p>.05). Mean nuclear area was 88.90 μm2 ± 19 in grade III and 72.30 μm2 ± 13.9 in grade II, with statistical difference between grades (P =.011). Mean nuclear perimeter was 32.40 ìm ± 3.0 in grade II and 35.70 ìm ± 4.0 in grade III, with statistical difference between grades (P =.018). Mean nuclear circumference factor was 1.0 ± 0.33 in grade II and 1.1 ± 0.28 in grade III, with no statistical difference between grades (P = 0.78). Nuclear-tocytoplasmic ratio in grade II was 0.29 ±.07 and 0.39 ±.08 in grade III, with statistical difference (P =.02). The number of binucleated and multinucleated cells and mitotic figures was significantly increased in grade III MCTs (P <.001). In conclusion, the number of mitotic figures, presence of binucleation and multinucleation, and nuclear-to-cytoplasmic ratio can help to guide a profile of MCT aggressiveness in cytologic preparations.

Optimizing optimum-path forest classification for huge datasets

Traditional pattern recognition techniques can not handle the classification of large datasets with both efficiency and effectiveness. In this context, the Optimum-Path Forest (OPF) classifier was recently introduced, trying to achieve high recognition rates and low computational cost. Although OPF was much faster than Support Vector Machines for training, it was slightly slower for classification. In this paper, we present the Efficient OPF (EOPF), which is an enhanced and faster version of the traditional OPF, and validate it for the automatic recognition of white matter and gray matter in magnetic resonance images of the human brain. © 2010 IEEE.

Fast petroleum well drilling monitoring through optimum-path forest

Automatic inspection of petroleum well drilling has became paramount in the last years, mainly because of the crucial importance of saving time and operations during the drilling process in order to avoid some problems, such as the collapse of the well borehole walls. In this paper, we extended another work by proposing a fast petroleum well drilling monitoring through a modified version of the Optimum-Path Forest classifier. Given that the cutting's volume at the vibrating shale shaker can provide several information about drilling, we used computer vision techniques to extract texture informations from cutting images acquired by a digital camera. A collection of supervised classifiers were applied in order to allow comparisons about their accuracy and effciency. We used the Optimum-Path Forest (OPF), EOPF (Efficient OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP) Support Vector Machines (SVM), and a Bayesian Classifier (BC) to assess the robustness of our proposed schema for petroleum well drilling monitoring through cutting image analysis.

Precipitates segmentation from scanning electron microscope images through machine learning techniques

The presence of precipitates in metallic materials affects its durability, resistance and mechanical properties. Hence, its automatic identification by image processing and machine learning techniques may lead to reliable and efficient assessments on the materials. In this paper, we introduce four widely used supervised pattern recognition techniques to accomplish metallic precipitates segmentation in scanning electron microscope images from dissimilar welding on a Hastelloy C-276 alloy: Support Vector Machines, Optimum-Path Forest, Self Organizing Maps and a Bayesian classifier. Experimental results demonstrated that all classifiers achieved similar recognition rates with good results validated by an expert in metallographic image analysis. © 2011 Springer-Verlag Berlin Heidelberg.

Flexibility and torsional resistance of three nickel-titanium retreatment instrument systems

Aim To assess the dimensional characteristics, flexibility and torsional behaviour of nickel-titanium retreatment instruments. Methodology Using image analysis software and high-resolution digital images, the instrument length, tip angle, diameter at 3mm from the tip and the distance between the blades (pitch length) of the following eight instruments were measured (n=12 for each measurement parameter): the ProTaper Universal retreatment (PTU-R) D1, D2 and D3 instruments; the R-Endo R1, R2 and R3 retreatment instruments; and the Mtwo retreatment (Mtwo-R) sizes 25 and 15 retreatment instruments. Maximum torque and the angular deflection at fracture as well as the bending moment at 45° were measured (n=12) according to the International Standards Organisation (ISO) specification number 3630-1. Data were analysed using the analysis of variance (α=0.05). Results The length of the active part of the instruments was found to vary according to the depth of the canal into which they were designed to reach. The pitch length also increased along the active length. The PTU-R D1 and the Mtwo-R instruments had active tips. Measurements of the bending moment at 45° revealed that the Mtwo-R 15 instrument was the most flexible, whereas the PTU-R D1 was the least flexible. The maximum torque tended to increase as the instrument diameter at 3mm from the tip increased, whereas the angular deflection at fracture varied in the opposite direction. Conclusions The geometrical characteristics of the retreatment instruments and their flexibility and torsion behaviour were consistent with their intended clinical application. © 2011 International Endodontic Journal.

Um filtro gaussiano adaptativo para análise comparativa de imagens de radares e satélites meteorológicos

Meteorological satellite and radar data comparative analysis allows to correlate the precipitation structures observed in both images. Such analysis would make feasible the extension of the range of ground-based meteorological radars. In addition to the different spatial and temporal resolution of these images this comparative analysis presents difficulties due to the effects of rotation and distortion, besides the different formats, projections, and coordinate systems. This work employed an approach based on a Gaussian adaptive filter in order to compare such images. The statistical results obtained from the comparison of the images are matched to those produced by other methods.

A graph-based framework for thermal faceprint characterization

Thermal faceprint has been paramount in the last years. Since we can handle with face recognition using images acquired in the infrared spectrum, an unique individual's signature can be obtained through the blood vessels network of the face. In this work, we propose a novel framework for thermal faceprint extraction using a collection of graph-based techniques, which were never used to this task up to date. A robust method of thermal face segmentation is also presented. The experiments, which were conducted over the UND Collection C dataset, have showed promising results. © 2011 Springer-Verlag.

A Markov random field model for combining optimum-path forest classifiers using decision graphs and game strategy approach

The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed rules and decision templates are often used. Therefore, the influence and relationship between classifier decisions are often not considered in the combination schemes. In this paper we propose a framework to combine classifiers using a decision graph under a random field model and a game strategy approach to obtain the final decision. The results of combining Optimum-Path Forest (OPF) classifiers using the proposed model are reported, obtaining good performance in experiments using simulated and real data sets. The results encourage the combination of OPF ensembles and the framework to design multiple classifier systems. © 2011 Springer-Verlag.

Porosidade e infiltração de água do solo sob diferentes sistemas de manejo

Management systems affect soil structure, causing changes in porosity that can influence water infiltration into the soil. This study aimed to evaluate the effect of different management systems on the porosity and water infiltration in Distroferric Red Nitosol with clay texture. The management systems were: conventional with disc plow + two soft harrowing, conventional with heavy disc harrow + two soft harrowing, no tillage and fallow. The following attributes: porosity, pore shape and water infiltration velocity into the soil were determined. Management systems such as no-tillage, conventional with disc plow and heavy disc harrow, and fallow modify the porosity and the shape of pores of a Distroferric Red Nitosol, influencing water infiltration, which was favored in no-tillage for the greater presence of elongated pores.

Automatic visual dictionary generation through Optimum-Path Forest clustering

Image categorization by means of bag of visual words has received increasing attention by the image processing and vision communities in the last years. In these approaches, each image is represented by invariant points of interest which are mapped to a Hilbert Space representing a visual dictionary which aims at comprising the most discriminative features in a set of images. Notwithstanding, the main problem of such approaches is to find a compact and representative dictionary. Finding such representative dictionary automatically with no user intervention is an even more difficult task. In this paper, we propose a method to automatically find such dictionary by employing a recent developed graph-based clustering algorithm called Optimum-Path Forest, which does not make any assumption about the visual dictionary's size and is more efficient and effective than the state-of-the-art techniques used for dictionary generation. © 2012 IEEE.

Persistence of epoxy-based sealer residues in dentin treated with different chemical removal protocols

The presence of residual endodontic sealer in the pulp chamber may cause discoloration of the dental crown and interfere with the adhesion of restorative materials. The aim of this study was to compare the efficacy of different solvents in removing residues of an epoxy resin-based sealer (AH Plus) from the dentin walls of the pulp chamber, by scanning electron microscopy (SEM). Forty-four bovine incisor dental crown fragments were treated with 17% EDTA and 2.5% NaOCl. Specimens received a coating of AH Plus and were left undisturbed for 5 min. Then, specimens were divided in four groups (n = 10) and cleaned with one of the following solutions: isopropyl alcohol, 95% ethanol, acetone solution, or amyl acetate solution. Negative controls (n = 2) did not receive AH Plus, while in positive controls (n = 2) the sealer was not removed. AH Plus removal was evaluated by SEM, and a score system was applied. Data were analyzed by Kruskal-Wallis and Dunn tests. None of the solutions tested was able to completely remove AH Plus from the dentin of the pulp chamber. Amyl acetate performed better than 95% ethanol and isopropyl alcohol (p < 0.05), but not better than acetone (p > 0.05) in removing the sealer from dentin. No significant differences were observed between acetone, 95% ethanol, and isopropyl alcohol (p > 0.05). It was concluded that amyl acetate and acetone may be good options for cleaning the pulp chamber after obturation with AH Plus. SCANNING 35:17-21, 2013. © 2012 Wiley Periodicals, Inc. © Wiley Periodicals, Inc.

Effects of LLLT in combination with bisphosphonate on bone healing in critical size defects: A histological and histometric study in rat calvaria

The purpose of this study was to analyze histologically the effect of low-level laser therapy (LLLT) in combination with bisphosphonate on bone healing in surgically created critical size defects (CSD) in rat calvaria. One hundred Wistar female rats sham operated (sham) and ovariectomized (Ovx) were maintained untreated for 1 month to allow for the development of osteopenia in the Ovx animals. A CSD was made in the calvarium of each rat, and the animals were divided into five groups according to following treatments: (1) sham rats (control), (2) Ovx rats, (3) Ovx rats treated with LLLT, (4) Ovx rats treated with bisphosphonate, and (5) Ovx rats treated with bisphosphonate and LLLT. Groups 4 and 5 were irrigated with 1 ml of bisphosphonate, and groups 3 and 5 were submitted to LLLT (GaAlAs), 660 nm, 24 J, and 0.4285 W/cm2 on the CSD. Ten animals of each treatment were killed at 30 and 60 days. Histomorphometric assessments, using image analysis software, and histological analyses were performed. No defect was completely regenerated with the bone. Histometrically, it can be observed that groups 3 (37.49 ± 1.94%, 43.11 ± 2.39%) and 5 (35.05 ± 1.57%, 41.07 ± 1.89%) showed a significant bone neoformation when compared to groups 1 (16.81 ± 1.57%, 27.54 ± 1.49%), 2 (11.68 ± 0.98%, 22.51 ± 1.05%), and 4 (14.62 ± 1.70%, 25.67 ± 1.41%) in all experimental periods (P < 0.05). It was possible to conclude that the LLLT associated or not with bisphosphonate treatment was effective for stimulating bone formation in CSD in the calvaria of rats submitted to ovariectomy. © 2012 Springer-Verlag London Ltd.

Ki-67 labeling in canine perianal glands neoplasms: A novel approach for immunohistological diagnostic and prognostic

Background: The antibody Ki-67 is a reliable and easy tool to accurately assess the growth fraction of neoplasms in humans and animals, and it has been used to predict the clinical outcome. Therefore, the aim of the present study was to investigate the immunohistochemical expression pattern of Ki-67 in normal and neoplastic perianal glands of dogs to evaluate the possible use of this proliferation marker as an ancillary method of perianal tumor diagnosis. We studied 42 cases of perianal gland neoplasms including adenomas (n = 15), epitheliomas (n = 15), and carcinomas (n = 12). As controls, 13 tissue samples from normal perianal glands were used. A Ki-67 index was established by a computer-assisted image analysis and compared with manual counting. Results: Out of the 42 cases of perianal gland neoplasms, 34 were from males and eight from females. Recurrence was reported in 14 cases, being higher (8/12) in carcinomas. Immunostaining for Ki-67 revealed that the carcinomas showed a higher proliferation rate (9.87%) compared to groups of epitheliomas (2.66%) and adenomas (0.36%). For adenomas and epitheliomas of the perianal glands the computer-assisted counting and the manual counting gave similar results; however, only the computer-assisted image analysis was efficient to predict the perianal gland carcinoma recurrence.Conclusion: Since there were significant differences in the number of Ki-67-positive nuclei, this marker proved to be effective in helping the classification of perianal gland neoplasms and to refine the diagnosis criteria, especially in those samples with high variation in morphology/area. Also, higher Ki-67 index is related to recurrence in cases of perianal gland carcinomas. Further, the computer-assisted image analysis proved to be a fast and reliable method to assess the Ki-67 index in perianal gland neoplasms. © 2013 Pereira et al.; licensee BioMed Central Ltd.

A computer vision approach to quantify leaf anatomical plasticity: A case study on gochnatia polymorpha (less.) cabrera

Inferences about leaf anatomical characteristics had largely been made by manually measuring diverse leaf regions, such as cuticle, epidermis and parenchyma to evaluate differences caused by environmental variables. Here we tested an approach for data acquisition and analysis in ecological quantitative leaf anatomy studies based on computer vision and pattern recognition methods. A case study was conducted on Gochnatia polymorpha (Less.) Cabrera (Asteraceae), a Neotropical savanna tree species that has high phenotypic plasticity. We obtained digital images of cross-sections of its leaves developed under different light conditions (sun vs. shade), different seasons (dry vs. wet) and in different soil types (oxysoil vs. hydromorphic soil), and analyzed several visual attributes, such as color, texture and tissues thickness in a perpendicular plane from microscopic images. The experimental results demonstrated that computational analysis is capable of distinguishing anatomical alterations in microscope images obtained from individuals growing in different environmental conditions. The methods presented here offer an alternative way to determine leaf anatomical differences. © 2013 Elsevier B.V.

Escala diagramática para quantificação da severidade de manchas em folhas de Eucalyptus globulus Labill. causadas por Teratosphaeria nubilosa (Cooke) Crous & U. Braun

The leaf spot (Mycosphaerella leaf disease = MLD) caused by Teratosphaeria nubilosa has caused damage in eucalypt plantations in southern and southeastern Brazil. The need to assess the disease in the field to evaluate of this damage, efficiency control, evaluation of germplasm induces to the necessity of having a visual scale for evaluation of disease. The objective was to develop a diagrammatic scale for young leaves and one for adult leaves of Eucalyptus globules for MLD. To do so, the leaves collected in the field were scanned for image analysis. The damaged area, the healthy leaf area and the external area of the same scale RGB (Red, Green, Blue) were determined. Subsequently, it was determinate the levels of severity depending on the sample distribution with seven levels for young leaves and six for adult leaves. For the visual acuity test and validate the scale, the leaves were evaluated for severity, with and without scale. With this proposed scales, the assessors showed good accuracy both for young and adult leaves with R2=0,98 and R2=0,80, respectively. The importance of the development of diagrammatic scales for assessing MLD in eucalyptus must to the fact that allows quantification of the symptoms accurately and precisely.