Radiopacity evaluation of root-end filling materials by digitization of images

The purpose of this study was to evaluate the radiopacity of 5 root-end filling materials (white MTA-Angelus, grey MTA-Angelus, IRM, Super EBA and Sealer 26). Five specimens (10 mm diameter X 1 mm thickness) were made from each material and radiographed next to an aluminum stepwedge varying in thickness from 2 to 16 mm. Radiographs were digitized and the radiopacity of the materials was compared to that of the aluminum stepwedge using VIXWIN 2000 software in millimeters of aluminum ( mm Al). Data were analyzed statistically by ANOVA and Tukey's test at 5% significance level. Radiopacity values varied from 3 mm Al to 5.9 mm Al. Sealer 26 and IRM presented the highest radiopacity values (p<0.05), while white/grey MTA and Super EBA presented the lowest radiopacity values (p<0.05). The tested root- end filling materials presented different radiopacities, white/grey MTA and Super EBA being the least radiopaque materials.

Level of insight and clinical features of obsessive-compulsive disorder with and without body dysmorphic disorder

Introduction: Body dysmorphic disorder (BDD) and obsessive-compulsive disorder (OCD) have several similarities and are included among the obsessive-compulsive spectrum of disorders. However, the content of preoccupations and level of insight of BDD patients differ from OCD patients. Objective: To compare the level of insight regarding obsessive-compulsive symptoms (OCS) and other clinical features in OCD patients with and without comorbid BDD. Methods: We evaluated 103 OCD patients (n=25, comorbid BDD), according to Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria using the Structured Clinical Interview for DSM-IV, the Yale-Brown Obsessive-Compulsive Scale, the University of Sao Paulo Sensory Phenomena Scale, the Beck Depression and Anxiety Inventories, and the Brown Assessment of Beliefs Scale. Resylts: The study groups differed significantly on several clinical features, including level of insight. A worse level of insight regarding OCS was independently associated with the presence of comorbid BDD. Lower educational level, more psychiatric comorbidities, presence of somatic and hoarding obsessions, and presence of intrusive images were associated with BDD comorbidity, even after adjusting for possible confounders. Conclusion: The presence of BDD in OCD patients is associated with poorer insight into obsessional beliefs and higher morbidity, reflected by lower educational levels and higher number of psychiatric comorbid disorders in general.

Bone mineral density on conventional and digitized images under different parameters of digitization and storage

Aim: To assess the bone mineral density on conventional and digitized images, comparing whether different parameters of digitization and storage change these values. Methods: Twenty radiographs were taken from five partially dentulous dry mandibles with an aluminum 7-mm stepwedge placed on the superior edge of the film. After processing, the films were digitized with a resolution of 600 and 2,400 d.p.i. and saved as TIFF and JPEG files. On every conventional and digitized image, circular regions of interest were selected for densitometry and radiographic contrast analysis. Results: Pearson's correlation coefficient showed a significant and strong mean gray values association between digitized and conventional images, differing from radiographic contrast that did not show a significant association. ANOVA did not reveal a statistically significant difference in bone density and radiographic contrast among the four digitized image groups, but the conventional image contrast was significantly lower. Conclusions: Bone mineral density did not differ in both conventional and digitized images. The parameters of image compression and resolution, tested in this study, did not change the results of densitometry and digitization process increased the radiographic contrast.

Performance of the CMS Level-1 trigger during commissioning with cosmic ray muons and LHC beams

The CMS Level-1 trigger was used to select cosmic ray muons and LHC beam events during data-taking runs in 2008, and to estimate the level of detector noise. This paper describes the trigger components used, the algorithms that were executed, and the trigger synchronisation. Using data from extended cosmic ray runs, the muon, electron/photon, and jet triggers have been validated, and their performance evaluated. Efficiencies were found to be high, resolutions were found to be good, and rates as expected. © 2010 IOP Publishing Ltd and SISSA.

Commissioning of the CMS High-Level Trigger with cosmic rays

The CMS High-Level Trigger (HLT) is responsible for ensuring that data samples with potentially interesting events are recorded with high efficiency and good quality. This paper gives an overview of the HLT and focuses on its commissioning using cosmic rays. The selection of triggers that were deployed is presented and the online grouping of triggered events into streams and primary datasets is discussed. Tools for online and offline data quality monitoring for the HLT are described, and the operational performance of the muon HLT algorithms is reviewed. The average time taken for the HLT selection and its dependence on detector and operating conditions are presented. The HLT performed reliably and helped provide a large dataset. This dataset has proven to be invaluable for understanding the performance of the trigger and the CMS experiment as a whole. © 2010 IOP Publishing Ltd and SISSA.

Computer techniques towards the automatic characterization of graphite particles in metallographic images of industrial materials

The automatic characterization of particles in metallographic images has been paramount, mainly because of the importance of quantifying such microstructures in order to assess the mechanical properties of materials common used in industry. This automated characterization may avoid problems related with fatigue and possible measurement errors. In this paper, computer techniques are used and assessed towards the accomplishment of this crucial industrial goal in an efficient and robust manner. Hence, the use of the most actively pursued machine learning classification techniques. In particularity, Support Vector Machine, Bayesian and Optimum-Path Forest based classifiers, and also the Otsu's method, which is commonly used in computer imaging to binarize automatically simply images and used here to demonstrated the need for more complex methods, are evaluated in the characterization of graphite particles in metallographic images. The statistical based analysis performed confirmed that these computer techniques are efficient solutions to accomplish the aimed characterization. Additionally, the Optimum-Path Forest based classifier demonstrated an overall superior performance, both in terms of accuracy and speed. © 2012 Elsevier Ltd. All rights reserved.

Wavelets in the computed evaluation of mammographic accreditation phantom images

This paper presents a novel approach to the computed assessment of a mammographic phantom device. The approach shown here is fully automated and is based on the automatic selection of the region of interest, in the use of the discrete wavelet transform (DWT) and morphological operators to assess the quality of the American College of Radiology (ACR) mammographic phantom images. The algorithms developed here have succesfully scored 30 images obtained with different combinations of voltage applied to the tube and exposure and could notice the differences in the radiographs due to the different level of exposure to radiation. © 2013 Springer-Verlag.

Processamento digital de imagens para identificação da sigatoka negra em bananais utilizando análise de componentes principais e redes neurais artificiais

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Fractal dimension of the mandibular trabecular bone measured on digital and digitized images.

Aims: This study compared fractal dimension (FD) values on mandibular trabecular bone in digital and digitized images at different spatial and contrast resolutions. Materials and Methods: 12 radiographs of dried human mandibles were obtained using custom-fabricated hybrid image receptors composed of a periapical radiographic film and a photostimulable phosphor plate (PSP). The film/ PSP sets were disassembled, and the PSPs produced images with 600 dots per inch (dpi) and 16 bits. These images were exported as tagged image file format (TIFF), 16 and 8 bits, and 600, 300 and 150 dpi. The films were processed and digitized 3 times on a flatbed scanner, producing TIFF images with 600, 300 and 150 dpi, and 8 bits. On each image, a circular region of interest was selected on the trabecular alveolar bone, away from root apices and FD was calculated by tile counting method. Two-way ANOVA and Tukey’s test were conducted to compare the mean values of FD, according to image type and spatial resolution (α = 5%). Results: Spatial resolution was directly and inversely proportional to FD mean values and standard deviation, respectively. Spatial resolution of 150 dpi yielded significant lower mean values of FD than the resolutions of 600 and 300 dpi ( P < 0.05). A nonsignificant variability was observed for the image types ( P > 0.05). The interaction between type of image and level of spatial resolution was not signi fi cant (P > 0.05). Conclusion: Under the tested, conditions, FD values of the mandibular trabecular bone assessed either by digital or digitized images did not change. Furthermore, these values were in fluenced by lower spatial resolution but not by contrast resolution.

Estimation of chlorophyll-a concentration and the trophic state of the Barra Bonita hydroelectric reservoir using oli/landsat-8 images

Reservoirs are artificial environments built by humans, and the impacts of these environments are not completely known. Retention time and high nutrient availability in the water increases the eutrophic level. Eutrophication is directly correlated to primary productivity by phytoplankton. These organisms have an important role in the environment. However, high concentrations of determined species can lead to public health problems. Species of cyanobacteria produce toxins that in determined concentrations can cause serious diseases in the liver and nervous system, which could lead to death. Phytoplankton has photoactive pigments that can be used to identify these toxins. Thus, remote sensing data is a viable alternative for mapping these pigments, and consequently, the trophic. Chlorophyll-a (Chl-a) is present in all phytoplankton species. Therefore, the aim of this work was to evaluate the performance of images of the sensor Operational Land Imager (OLI) onboard the Landsat-8 satellite in determining Chl-a concentrations and estimating the trophic level in a tropical reservoir. Empirical models were fitted using data from two field surveys conducted in May and October 2014 (Austral Autumn and Austral Spring, respectively). Models were applied in a temporal series of OLI images from May 2013 to October 2014. The estimated Chl-a concentration was used to classify the trophic level from a trophic state index that adopted the concentration of this pigment-like parameter. The models of Chl-a concentration showed reasonable results, but their performance was likely impaired by the atmospheric correction. Consequently, the trophic level classification also did not obtain better results.