Hyperplane navigation: A method to set individual scores in fMRI group datasets

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.

Classification System of Raman Spectra using Cluster Analysis to Diagnose Coronary Artery Lesions

The traditional methods employed to detect atherosclerotic lesions allow for the identification of lesions; however, they do not provide specific characterization of the lesion`s biochemistry. Currently, Raman spectroscopy techniques are widely used as a characterization method for unknown substances, which makes this technique very important for detecting atherosclerotic lesions. The spectral interpretation is based on the analysis of frequency peaks present in the signal; however, spectra obtained from the same substance can show peaks slightly different and these differences make difficult the creation of an automatic method for spectral signal analysis. This paper presents a signal analysis method based on a clustering technique that allows for the classification of spectra as well as the inference of a diagnosis about the arterial wall condition. The objective is to develop a computational tool that is able to create clusters of spectra according to the arterial wall state and, after data collection, to allow for the classification of a specific spectrum into its correct cluster.

Safety Profile of Trocar and Insufflation Needle Access Systems in Laparoscopic Surgery

BACKGROUND: The most common laparoscopic complications are associated with trocar insertion. The purpose of this study was to develop an objective method of evaluating the safety profile of various access devices used in laparoscopic surgery. STUDY DESIGN: In 20 swine, 6 bladed and 2 needle access devices were evaluated. A force profile was determined by measuring the force required to drive the trocar or needle through the fascia and into the peritoneum, at 0 and 10 mmHg. The amount Of tissue deformation, the length of blade exposed, and the duration of exposure were measured using a high-speed digital imaging system. RESULTS: The needle system without the sheath required the least driving force and had the most favorable force profile. In contrast, the bladed, nonretractable trocar system required a higher driving force and a rapid loss of resistance. Insertion under a pneumoperitoneum did not significantly alter the force profile of the various access devices except for the amount of tissue deformation. With the bladed system, the blade itself was exposed for an average of 0.5 to 1.0 seconds for a distance of 4.5 to 5.0 cm. In comparison, the needle system was exposed for 0.2 seconds for a distance of 1.8 cm. CONCLUSIONS: We developed a reproducible method of measuring the forces required to place the access systems, their pattern of resistance loss, and the characteristics of the blade exposure. These parameters may provide an adjunctive and objective measurement of safety, allowing for more direct comparison between various trocar designs. (J Am Coll Surg 2009;209:222-232. (C) 2009 by the American College of Surgeons)

Comparative study of Botox (R) injection treatment for upper eyelid retraction with 6-month follow-up in patients with thyroid eye disease in the congestive or fibrotic stage

Aim To compare morphometric data of the eyelid fissure and the levator muscle function (LF) before and up to 6 months after transcutaneous injection with five units of Botox (R) in patients with upper lid retraction (ULR) from congestive or fibrotic thyroid eye disease (TED). Methods Twenty-four patients with ULR from TED were submitted to transcutaneous injection of 5 units (0.1 ml) of Botox in one eye only. Patients were divided into two groups: 12 with congestive-stage TED (CG), and 12 with fibrotic-stage TED (FG). Bilateral lid fissure measurements using digital imaging and computer-aided analysis were taken at baseline and at regular intervals 2 weeks, 1 month, 3 months and 6 months after unilateral Botox injection. Mean values taken at different follow-up points were compared for the two groups. Results Most patients experienced marked improvement in ULR, with a mean reduction of 3.81 mm in FG and 3.05 mm in CG. The upper eyelid margin reflex distance, fissure height and total area of exposed interpalpebral fissure were significantly smaller during 1 month in CG and during 3 months in FG. Reduction in LF and in the difference between lateral and medial lid fissure measurements was observed in both groups. The treatment lasted significantly longer in FG than in CG. Conclusions A single 5-unit Botox injection improved ULR, reduced LF and produced an adequate lid contour in patients with congestive or fibrotic TED. The effect lasts longer in patients with fibrotic orbitopathy than in patients with congestive orbitopathy.

Prevention of toothbrushing abrasion of acid-softened enamel by CO(2) laser irradiation

Objective: The aim of the present study was to evaluate the effect of CO(2) laser irradiation (10.6 mu m) at 0.3 J/cm(2) (0.5 mu s; 226 Hz) on the resistance of softened enamel to toothbrushing abrasion, in vitro. Methods: Sixty human enamel samples were obtained, polished with silicon carbide papers and randomly divided into five groups (n = 12), receiving 5 different surface treatments: laser irradiation (L), fluoride (AmF/NaF gel) application (F), laser prior to fluoride (LF), fluoride prior to laser (FL), non-treated control (C). After surface treatment they were submitted to a 25-day erosive-abrasive cycle in 100 ml sprite light (90 s) and brushed twice daily with an electric toothbrush. Between the demineralization periods samples were immersed in supersaturated mineral solution. At the end of the experiments enamel surface loss was determined using a contact profilometer and morphological analysis was performed using scanning electron microscopy (SEM). For SEM analysis of demineralization pattern, cross-sectional cuts of cycled samples were prepared. The data were statistically analysed by one-way ANOVA model with subsequent pairwise comparison of treatments. Results: Abrasive surface loss was significantly lower in all laser groups compared to both control and fluoride groups (p < 0.0001 in all cases). Amongst the laser groups no significant difference was observed. Softened enamel layer underneath lesions was less pronounced in laser-irradiated samples. Conclusion: Irradiation of dental enamel with a CO(2) laser at 0.3 J/cm(2) (5 mu s, 226 Hz) either alone or in combination with amine fluoride gel significantly decreases toothbrushing abrasion of softened-enamel, in vitro. (C) 2011 Elsevier Ltd. All rights reserved.

Effect of image compression of digital lateral cephalograms on the reproducibility of cephalometric points

Objectives: To evaluate the influence of JPEG quality factors 100, 80 and 60 on the reproducibility of identification of cephalometric points on images of lateral cephalograms, compared with the Digital Imaging and Communications in Medicine (DICOM) format. Methods: The sample was composed of 30 images of digital lateral cephalograms obtained from 30 individuals (15 males and 15 females) on a phosphor plate system in DICOM format. The images were converted to JPEG with quality factors 100, 80 and 60 with the aid of software, adding up to 90 images. The 120 images (DICOM, JPEG 100, 80 and 60) were blinded and 12 cephalometric points were identified on each image by three calibrated orthodontists, using the x-y coordinate system, on a cephalometric software. Results: The results revealed that identification of cephalometric points was highly reproducible, except for the point Orbitale (Or) on the x-axis. The different file formats did not present a statistically significant difference. Conclusions: JPEG images of lateral cephalograms with quality factors 100, 80 and 60 did not present alterations in the reproducibility of identification of cephalometric points compared with the DICOM format. Good reproducibility was achieved for the 12 points, except for point Or on the x-axis. Dentomaxillofacial Radiology (2009) 38, 393-400. doi: 10.1259/dmfr/40996636

Morphological properties of superclusters of galaxies

We studied superclusters of galaxies in a volume-limited sample extracted from the Sloan Digital Sky Survey Data Release 7 and from mock catalogues based on a semi-analytical model of galaxy evolution in the Millennium Simulation. A density field method was applied to a sample of galaxies brighter than M(r) = -21+5 log h(100) to identify superclusters, taking into account selection and boundary effects. In order to evaluate the influence of the threshold density, we have chosen two thresholds: the first maximizes the number of objects (D1) and the second constrains the maximum supercluster size to similar to 120 h(-1) Mpc (D2). We have performed a morphological analysis, using Minkowski Functionals, based on a parameter, which increases monotonically from filaments to pancakes. An anticorrelation was found between supercluster richness (and total luminosity or size) and the morphological parameter, indicating that filamentary structures tend to be richer, larger and more luminous than pancakes in both observed and mock catalogues. We have also used the mock samples to compare supercluster morphologies identified in position and velocity spaces, concluding that our morphological classification is not biased by the peculiar velocities. Monte Carlo simulations designed to investigate the reliability of our results with respect to random fluctuations show that these results are robust. Our analysis indicates that filaments and pancakes present different luminosity and size distributions.

Visual analysis of image collections

Multidimensional Visualization techniques are invaluable tools for analysis of structured and unstructured data with variable dimensionality. This paper introduces PEx-Image-Projection Explorer for Images-a tool aimed at supporting analysis of image collections. The tool supports a methodology that employs interactive visualizations to aid user-driven feature detection and classification tasks, thus offering improved analysis and exploration capabilities. The visual mappings employ similarity-based multidimensional projections and point placement to layout the data on a plane for visual exploration. In addition to its application to image databases, we also illustrate how the proposed approach can be successfully employed in simultaneous analysis of different data types, such as text and images, offering a common visual representation for data expressed in different modalities.

Topological multi-contour decomposition for image analysis and image retrieval

Successful classification, information retrieval and image analysis tools are intimately related with the quality of the features employed in the process. Pixel intensities, color, texture and shape are, generally, the basis from which most of the features are Computed and used in such fields. This papers presents a novel shape-based feature extraction approach where an image is decomposed into multiple contours, and further characterized by Fourier descriptors. Unlike traditional approaches we make use of topological knowledge to generate well-defined closed contours, which are efficient signatures for image retrieval. The method has been evaluated in the CBIR context and image analysis. The results have shown that the multi-contour decomposition, as opposed to a single shape information, introduced a significant improvement in the discrimination power. (c) 2008 Elsevier B.V. All rights reserved,

Scalable model-based configuration management of security services in complex enterprise networks

Security administrators face the challenge of designing, deploying and maintaining a variety of configuration files related to security systems, especially in large-scale networks. These files have heterogeneous syntaxes and follow differing semantic concepts. Nevertheless, they are interdependent due to security services having to cooperate and their configuration to be consistent with each other, so that global security policies are completely and correctly enforced. To tackle this problem, our approach supports a comfortable definition of an abstract high-level security policy and provides an automated derivation of the desired configuration files. It is an extension of policy-based management and policy hierarchies, combining model-based management (MBM) with system modularization. MBM employs an object-oriented model of the managed system to obtain the details needed for automated policy refinement. The modularization into abstract subsystems (ASs) segment the system-and the model-into units which more closely encapsulate related system components and provide focused abstract views. As a result, scalability is achieved and even comprehensive IT systems can be modelled in a unified manner. The associated tool MoBaSeC (Model-Based-Service-Configuration) supports interactive graphical modelling, automated model analysis and policy refinement with the derivation of configuration files. We describe the MBM and AS approaches, outline the tool functions and exemplify their applications and results obtained. Copyright (C) 2010 John Wiley & Sons, Ltd.

Texture analysis and classification using deterministic tourist walk

In this paper, we present a study on a deterministic partially self-avoiding walk (tourist walk), which provides a novel method for texture feature extraction. The method is able to explore an image on all scales simultaneously. Experiments were conducted using different dynamics concerning the tourist walk. A new strategy, based on histograms. to extract information from its joint probability distribution is presented. The promising results are discussed and compared to the best-known methods for texture description reported in the literature. (C) 2009 Elsevier Ltd. All rights reserved.

Texture analysis using graphs generated by deterministic partially self-avoiding walks

Texture is one of the most important visual attributes for image analysis. It has been widely used in image analysis and pattern recognition. A partially self-avoiding deterministic walk has recently been proposed as an approach for texture analysis with promising results. This approach uses walkers (called tourists) to exploit the gray scale image contexts in several levels. Here, we present an approach to generate graphs out of the trajectories produced by the tourist walks. The generated graphs embody important characteristics related to tourist transitivity in the image. Computed from these graphs, the statistical position (degree mean) and dispersion (entropy of two vertices with the same degree) measures are used as texture descriptors. A comparison with traditional texture analysis methods is performed to illustrate the high performance of this novel approach. (C) 2011 Elsevier Ltd. All rights reserved.

An entropy-based approach to automatic image segmentation of satellite images

An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation. (C) 2010 Elsevier B.V. All rights reserved.

ENHANCING MULTISCALE FRACTAL DESCRIPTORS USING FUNCTIONAL DATA ANALYSIS

This work presents a novel approach in order to increase the recognition power of Multiscale Fractal Dimension (MFD) techniques, when applied to image classification. The proposal uses Functional Data Analysis (FDA) with the aim of enhancing the MFD technique precision achieving a more representative descriptors vector, capable of recognizing and characterizing more precisely objects in an image. FDA is applied to signatures extracted by using the Bouligand-Minkowsky MFD technique in the generation of a descriptors vector from them. For the evaluation of the obtained improvement, an experiment using two datasets of objects was carried out. A dataset was used of characters shapes (26 characters of the Latin alphabet) carrying different levels of controlled noise and a dataset of fish images contours. A comparison with the use of the well-known methods of Fourier and wavelets descriptors was performed with the aim of verifying the performance of FDA method. The descriptor vectors were submitted to Linear Discriminant Analysis (LDA) classification method and we compared the correctness rate in the classification process among the descriptors methods. The results demonstrate that FDA overcomes the literature methods (Fourier and wavelets) in the processing of information extracted from the MFD signature. In this way, the proposed method can be considered as an interesting choice for pattern recognition and image classification using fractal analysis.

Texture analysis based on maximum contrast walker

Recently, the deterministic tourist walk has emerged as a novel approach for texture analysis. This method employs a traveler visiting image pixels using a deterministic walk rule. Resulting trajectories provide clues about pixel interaction in the image that can be used for image classification and identification tasks. This paper proposes a new walk rule for the tourist which is based on contrast direction of a neighborhood. The yielded results using this approach are comparable with those from traditional texture analysis methods in the classification of a set of Brodatz textures and their rotated versions, thus confirming the potential of the method as a feasible texture analysis methodology. (C) 2010 Elsevier B.V. All rights reserved.