Orbitoethmoidal impacted injury by kitchen knife causing abducens nerve palsy

Introduction: Impacted knife injuries in the maxillofacial region are rare and infrequently reported. In cases of injury involving orbit or eye, these reports are even rarer. Discussion: Damage to the orbital contents may result in a rupture of the globe, extraocular muscle injury, lacrimal gland damage, and others. Orbital foreign bodies are not only difficult to detect, and clinical features vary according to its size, characteristics, shape, penetrating method, and site. In this report, a case of abducens nerve palsy after orbitoethmoidal knife injury is presented. © 2010 Springer-Verlag.

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.

Influence of apical enlargement in cleaning and extrusion in canals with mild and moderate curvatures

Optical microscopy and morphometric analysis were used in this study to evaluate, in vitro, the cleaning of the apical region in root canals with mild or moderate curvatures subjected to biomechanical preparation with a rotary system, as well as to assess the amount of extruded material to the periapical area. Lateral incisors (n = 32), 16 with curvature angles smaller or equal to 10° (GI) and 16 between 11° and 25° angles (GII) were submitted to Hero 642 rotary instrumentation with different surgical diameters: (A) 30.02 and (B) 45.02. Irrigation was performed at each change of instrument with 5 mL of ultrapure Milli-Q water and the extruded material through the apical foramen was collected. Root cross-sections were subjected to histological analysis by optical microscopy (×40) and the images were evaluated morphometrically using the Image Tool software. Quantification of the extruded material was performed by weighing after liquid evaporation. ANOVA showed no statistically significant differences (p>0.05) among the groups with respect to the procedures used to clean the apical region. Considering the amount of extruded material, the Tukey's HSD showed that canals with mild curvature prepared with the 45.02 surgical diameter showed significantly higher values (p<0.05) that those of the other groups, which were similar between themselves (p>0.05). In conclusion, the effect of cleaning the apical region did not differ in the groups, considering root curvature and the surgical diameter of instruments used for apical preparation. The amount of extruded material was greater in canals with mild curvature that were prepared with the 45.02 surgical instrument diameter.

Identification of foliar diseases in cotton crop

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.