A non-parametric vessel detection method for complex vascular structures

Modern medical imaging techniques enable the acquisition of in vivo high resolution images of the vascular system. Most common methods for the detection of vessels in these images, such as multiscale Hessian-based operators and matched filters, rely on the assumption that at each voxel there is a single cylinder. Such an assumption is clearly violated at the multitude of branching points that are easily observed in all, but the Most focused vascular image studies. In this paper, we propose a novel method for detecting vessels in medical images that relaxes this single cylinder assumption. We directly exploit local neighborhood intensities and extract characteristics of the local intensity profile (in a spherical polar coordinate system) which we term as the polar neighborhood intensity profile. We present a new method to capture the common properties shared by polar neighborhood intensity profiles for all the types of vascular points belonging to the vascular system. The new method enables us to detect vessels even near complex extreme points, including branching points. Our method demonstrates improved performance over standard methods on both 2D synthetic images and 3D animal and clinical vascular images, particularly close to vessel branching regions. (C) 2008 Elsevier B.V. All rights reserved.

Machine vision for the automatic classification of images acquired from Non-destructive tests

This project is based on Artificial Intelligence (A.I) and Digital Image processing (I.P) for automatic condition monitoring of sleepers in the railway track. Rail inspection is a very important task in railway maintenance for traffic safety issues and in preventing dangerous situations. Monitoring railway track infrastructure is an important aspect in which the periodical inspection of rail rolling plane is required.Up to the present days the inspection of the railroad is operated manually by trained personnel. A human operator walks along the railway track searching for sleeper anomalies. This monitoring way is not more acceptable for its slowness and subjectivity. Hence, it is desired to automate such intuitive human skills for the development of more robust and reliable testing methods. Images of wooden sleepers have been used as data for my project. The aim of this project is to present a vision based technique for inspecting railway sleepers (wooden planks under the railway track) by automatic interpretation of Non Destructive Test (NDT) data using A.I. techniques in determining the results of inspection.

Regulation and wage adjustment patterns : non parametric evidence from longitudinal data

This paper gives a first step toward a methodology to quantify the influences of regulation on short-run earnings dynamics. It also provides evidence on the patterns of wage adjustment adopted during the recent high inflationary experience in Brazil.The large variety of official wage indexation rules adopted in Brazil during the recent years combined with the availability of monthly surveys on labor markets makes the Brazilian case a good laboratory to test how regulation affects earnings dynamics. In particular, the combination of large sample sizes with the possibility of following the same worker through short periods of time allows to estimate the cross-sectional distribution of longitudinal statistics based on observed earnings (e.g., monthly and annual rates of change).The empirical strategy adopted here is to compare the distributions of longitudinal statistics extracted from actual earnings data with simulations generated from minimum adjustment requirements imposed by the Brazilian Wage Law. The analysis provides statistics on how binding were wage regulation schemes. The visual analysis of the distribution of wage adjustments proves useful to highlight stylized facts that may guide future empirical work.

Classification of lumber of Eucalyptus using non-destructive tests

Classification and standardization of the sawn wood is a usual activity, developed by countries that come as great consumers of this material. Brazil does not practice the classification of sawn wood. This work had the main objective of evaluating the sensibility of most common non-destructive tests in the classification of dimension lumber from fast grown Eucalyptus plantation. Wood was obtained from genetic material cultivated at Minas Gerais State, Brazil. 296 beams of structural dimensions (6 cm × 12 cm × 280 cm) from 10 different clones of Eucalyptus were sampled. Beams were non-destructively (stress wave, ultrasound and transverse vibration) and destructively (static bending and compression parallel to grain) tested. Non-destructive results showed sensibility in the classification of structural dimension lumber, being possible to establish wave velocity intervals that attend to the main strength classes reported by Wooden Structures Brazilian Code.

The dark matter profile of the Milky Way: a non-parametric reconstruction

We present the results of a new, non-parametric method to reconstruct the Galactic dark matter profile directly from observations. Using the latest kinematic data to track the total gravitational potential and the observed distribution of stars and gas to set the baryonic component, we infer the dark matter contribution to the circular velocity across the Galaxy. The radial derivative of this dynamical contribution is then estimated to extract the dark matter profile. The innovative feature of our approach is that it makes no assumption on the functional form or shape of the profile, thus allowing for a clean determination with no theoretical bias. We illustrate the power of the method by constraining the spherical dark matter profile between 2.5 and 25 kpc away from the Galactic center. The results show that the proposed method, free of widely used assumptions, can already be applied to pinpoint the dark matter distribution in the Milky Way with competitive accuracy, and paves the way for future developments.

Non-parametric identification of a non-linear buckled beam using discrete-time Volterra Series

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

Non-parametric estimation of the diffusion coefficient of a branching diffusion with immigration

Wir betrachten Systeme von endlich vielen Partikeln, wobei die Partikel sich unabhängig voneinander gemäß eindimensionaler Diffusionen [dX_t = b(X_t),dt + sigma(X_t),dW_t] bewegen. Die Partikel sterben mit positionsabhängigen Raten und hinterlassen eine zufällige Anzahl an Nachkommen, die sich gemäß eines Übergangskerns im Raum verteilen. Zudem immigrieren neue Partikel mit einer konstanten Rate. Ein Prozess mit diesen Eigenschaften wird Verzweigungsprozess mit Immigration genannt. Beobachten wir einen solchen Prozess zu diskreten Zeitpunkten, so ist zunächst nicht offensichtlich, welche diskret beobachteten Punkte zu welchem Pfad gehören. Daher entwickeln wir einen Algorithmus, um den zugrundeliegenden Pfad zu rekonstruieren. Mit Hilfe dieses Algorithmus konstruieren wir einen nichtparametrischen Schätzer für den quadrierten Diffusionskoeffizienten $sigma^2(cdot),$ wobei die Konstruktion im Wesentlichen auf dem Auffüllen eines klassischen Regressionsschemas beruht. Wir beweisen Konsistenz und einen zentralen Grenzwertsatz.

Mechanical non-surgical treatment of peri-implantitis: a single-blinded randomized longitudinal clinical study. II. Microbiological results

BACKGROUND: Peri-implantitis is common in patients with dental implants. We performed a single-blinded longitudinal randomized study to assess the effects of mechanical debridement on the peri-implant microbiota in peri-implantitis lesions. MATERIALS AND METHODS: An expanded checkerboard DNA-DNA hybridization assay encompassing 79 different microorganisms was used to study bacterial counts before and during 6 months following mechanical treatment of peri-implantitis in 17 cases treated with curettes and 14 cases treated with an ultrasonic device. Statistics included non-parametric tests and GLM multivariate analysis with p<0001 indicating significance and 80% power. RESULTS: At selected implant test sites, the most prevalent bacteria were: Fusobacterium nucleatum sp., Staphylococci sp., Aggregatibacter actinomycetemcomitans, Helicobacter pylori, and Tannerella forsythia. 30 min. after treatment with curettes, A. actinomycetemcomitans (serotype a), Lactobacillus acidophilus, Streptococcus anginosus, and Veillonella parvula were found at lower counts (p<0.001). No such differences were found for implants treated with the ultrasonic device. Inconsistent changes occurred following the first week. No microbiological differences between baseline and 6-month samples were found for any species or between treatment study methods in peri-implantitis. CONCLUSIONS: Both methods failed to eliminate or reduce bacterial counts in peri-implantitis. No group differences were found in the ability to reduce the microbiota in peri-implantitis.

Relevance of In-vitro Tests of Adhesive and Composite Dental Materials. A Review in 3 Parts. Part 2: Non-standardized tests of composite materials

Summary The first part of this review examined ISO approval requirements and in vitro testing. In the second part, non-standardized test methods for composite materials are presented and discussed. Physical tests are primarily described. Analyses of surface gloss and alterations, as well as aging simulations of dental materials are presented. Again, the importance of laboratory tests in determining clinical outcomes is evaluated. Differences in the measurement protocols of the various testing institutes and how these differences can in?uence the results are also discussed. Because there is no standardization of test protocols, the values determined by different institutes cannot be directly compared. However, the ranking of the tested materials should be the same if a valid protocol is applied by different institutes. The modulus of elasticity, the expansion after water sorption, and the polishability of the material are all clinically relevant, whereas factors measured by other test protocols may have no clinical correlation. The handling properties of the materials are highly dependent on operators' preferences. Therefore, no standard values can be given.

Non-phenotypic tests to detect and characterize antibiotic resistance mechanisms in Enterobacteriaceae

In the past 2 decades, we have observed a rapid increase of infections due to multidrug-resistant Enterobacteriaceae. Regrettably, these isolates possess genes encoding for extended-spectrum β-lactamases (e.g., blaCTX-M, blaTEM, blaSHV) or plasmid-mediated AmpCs (e.g., blaCMY) that confer resistance to last-generation cephalosporins. Furthermore, other resistance traits against quinolones (e.g., mutations in gyrA and parC, qnr elements) and aminoglycosides (e.g., aminoglycosides modifying enzymes and 16S rRNA methylases) are also frequently co-associated. Even more concerning is the rapid increase of Enterobacteriaceae carrying genes conferring resistance to carbapenems (e.g., blaKPC, blaNDM). Therefore, the spread of these pathogens puts in peril our antibiotic options. Unfortunately, standard microbiological procedures require several days to isolate the responsible pathogen and to provide correct antimicrobial susceptibility test results. This delay impacts the rapid implementation of adequate antimicrobial treatment and infection control countermeasures. Thus, there is emerging interest in the early and more sensitive detection of resistance mechanisms. Modern non-phenotypic tests are promising in this respect, and hence, can influence both clinical outcome and healthcare costs. In this review, we present a summary of the most advanced methods (e.g., next-generation DNA sequencing, multiplex PCRs, real-time PCRs, microarrays, MALDI-TOF MS, and PCR/ESI MS) presently available for the rapid detection of antibiotic resistance genes in Enterobacteriaceae. Taking into account speed, manageability, accuracy, versatility, and costs, the possible settings of application (research, clinic, and epidemiology) of these methods and their superiority against standard phenotypic methods are discussed.

Automatic Bandwidth Estimation Strategy for High-Quality Non-Parametric Modeling based Moving Object Detection

Here, a novel and efficient moving object detection strategy by non-parametric modeling is presented. Whereas the foreground is modeled by combining color and spatial information, the background model is constructed exclusively with color information, thus resulting in a great reduction of the computational and memory requirements. The estimation of the background and foreground covariance matrices, allows us to obtain compact moving regions while the number of false detections is reduced. Additionally, the application of a tracking strategy provides a priori knowledge about the spatial position of the moving objects, which improves the performance of the Bayesian classifier

Versatile Bayesian classifier for moving object detection by non-parametric background-foreground modeling

Along the recent years, several moving object detection strategies by non-parametric background-foreground modeling have been proposed. To combine both models and to obtain the probability of a pixel to belong to the foreground, these strategies make use of Bayesian classifiers. However, these classifiers do not allow to take advantage of additional prior information at different pixels. So, we propose a novel and efficient alternative Bayesian classifier that is suitable for this kind of strategies and that allows the use of whatever prior information. Additionally, we present an effective method to dynamically estimate prior probability from the result of a particle filter-based tracking strategy.