106 resultados para Distance-based techniques
em Université de Lausanne, Switzerland
Resumo:
This paper presents the evaluation results of the methods submitted to Challenge US: Biometric Measurements from Fetal Ultrasound Images, a segmentation challenge held at the IEEE International Symposium on Biomedical Imaging 2012. The challenge was set to compare and evaluate current fetal ultrasound image segmentation methods. It consisted of automatically segmenting fetal anatomical structures to measure standard obstetric biometric parameters, from 2D fetal ultrasound images taken on fetuses at different gestational ages (21 weeks, 28 weeks, and 33 weeks) and with varying image quality to reflect data encountered in real clinical environments. Four independent sub-challenges were proposed, according to the objects of interest measured in clinical practice: abdomen, head, femur, and whole fetus. Five teams participated in the head sub-challenge and two teams in the femur sub-challenge, including one team who tackled both. Nobody attempted the abdomen and whole fetus sub-challenges. The challenge goals were two-fold and the participants were asked to submit the segmentation results as well as the measurements derived from the segmented objects. Extensive quantitative (region-based, distance-based, and Bland-Altman measurements) and qualitative evaluation was performed to compare the results from a representative selection of current methods submitted to the challenge. Several experts (three for the head sub-challenge and two for the femur sub-challenge), with different degrees of expertise, manually delineated the objects of interest to define the ground truth used within the evaluation framework. For the head sub-challenge, several groups produced results that could be potentially used in clinical settings, with comparable performance to manual delineations. The femur sub-challenge had inferior performance to the head sub-challenge due to the fact that it is a harder segmentation problem and that the techniques presented relied more on the femur's appearance.
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Following their detection and seizure by police and border guard authorities, false identity and travel documents are usually scanned, producing digital images. This research investigates the potential of these images to classify false identity documents, highlight links between documents produced by a same modus operandi or same source, and thus support forensic intelligence efforts. Inspired by previous research work about digital images of Ecstasy tablets, a systematic and complete method has been developed to acquire, collect, process and compare images of false identity documents. This first part of the article highlights the critical steps of the method and the development of a prototype that processes regions of interest extracted from images. Acquisition conditions have been fine-tuned in order to optimise reproducibility and comparability of images. Different filters and comparison metrics have been evaluated and the performance of the method has been assessed using two calibration and validation sets of documents, made up of 101 Italian driving licenses and 96 Portuguese passports seized in Switzerland, among which some were known to come from common sources. Results indicate that the use of Hue and Edge filters or their combination to extract profiles from images, and then the comparison of profiles with a Canberra distance-based metric provides the most accurate classification of documents. The method appears also to be quick, efficient and inexpensive. It can be easily operated from remote locations and shared amongst different organisations, which makes it very convenient for future operational applications. The method could serve as a first fast triage method that may help target more resource-intensive profiling methods (based on a visual, physical or chemical examination of documents for instance). Its contribution to forensic intelligence and its application to several sets of false identity documents seized by police and border guards will be developed in a forthcoming article (part II).
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The use of the Internet now has a specific purpose: to find information. Unfortunately, the amount of data available on the Internet is growing exponentially, creating what can be considered a nearly infinite and ever-evolving network with no discernable structure. This rapid growth has raised the question of how to find the most relevant information. Many different techniques have been introduced to address the information overload, including search engines, Semantic Web, and recommender systems, among others. Recommender systems are computer-based techniques that are used to reduce information overload and recommend products likely to interest a user when given some information about the user's profile. This technique is mainly used in e-Commerce to suggest items that fit a customer's purchasing tendencies. The use of recommender systems for e-Government is a research topic that is intended to improve the interaction among public administrations, citizens, and the private sector through reducing information overload on e-Government services. More specifically, e-Democracy aims to increase citizens' participation in democratic processes through the use of information and communication technologies. In this chapter, an architecture of a recommender system that uses fuzzy clustering methods for e-Elections is introduced. In addition, a comparison with the smartvote system, a Web-based Voting Assistance Application (VAA) used to aid voters in finding the party or candidate that is most in line with their preferences, is presented.
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DNA-based techniques are important tools for species assignment, in particular when identification with morphological criteria is difficult. The aim of this study was to genetically determine the species identity of tree frogs (Hyla spp.) populations from western and northern Switzerland (Swiss Plateau), this area being frequently subjected to introductions of species or sub-species from south of the Alps. We sequenced 261 base pairs of the mitochondrial DNA cytochrome b gene from 24 samples of tree frogs from the Swiss Plateau, Ticino (southern Switzerland) and the Dombes region (Ain, France), and compared them with homologous sequences retrieved from DNA databases. The phylogenetic analyses revealed two distinct clades. The first one is represented by samples of Green tree frog (Hyla arborea) from the Swiss Plateau, France, Germany and Greece, confirming the current knowledge about the species' distribution. The second clade includes samples belonging to the Italian tree frog (Hyla intermedia) from south of the Alps (Ticino and Italy), and unexpectedly from the Grangettes site in western Switzerland. These results suggest the introduction of the Italian tree frog H. intermedia north of the Alps, and raise questions about the management of the Grangettes protected area.
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BACKGROUND: Both non-traumatic and traumatic spinal cord injuries have in common that a relatively minor structural lesion can cause profound sensorimotor and autonomous dysfunction. Besides treating the cause of the spinal cord injury the main goal is to restore lost function as far as possible. AIM: This article provides an overview of current innovative diagnostic (imaging) and therapeutic approaches (neurorehabilitation and neuroregeneration) aiming for recovery of function after non-traumatic and traumatic spinal cord injuries. MATERIAL AND METHODS: An analysis of the current scientific literature regarding imaging, rehabilitation and rehabilitation strategies in spinal cord disease was carried out. RESULTS: Novel magnetic resonance imaging (MRI) based techniques (e.g. diffusion-weighted MRI and functional MRI) allow visualization of structural reorganization and specific neural activity in the spinal cord. Robotics-driven rehabilitative measures provide training of sensorimotor function in a targeted fashion, which can even be continued in the homecare setting. From a preclinical point of view, defined stem cell transplantation approaches allow for the first time robust structural repair of the injured spinal cord. CONCLUSION: Besides well-established neurological and functional scores, MRI techniques offer the unique opportunity to provide robust and reliable "biomarkers" for restorative therapeutic interventions. Function-oriented robotics-based rehabilitative interventions alone or in combination with stem cell based therapies represent promising approaches to achieve substantial functional recovery, which go beyond current rehabilitative treatment efforts.
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ABSTRACT: q-Space-based techniques such as diffusion spectrum imaging, q-ball imaging, and their variations have been used extensively in research for their desired capability to delineate complex neuronal architectures such as multiple fiber crossings in each of the image voxels. The purpose of this article was to provide an introduction to the q-space formalism and the principles of basic q-space techniques together with the discussion on the advantages as well as challenges in translating these techniques into the clinical environment. A review of the currently used q-space-based protocols in clinical research is also provided.
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The cichlids of East Africa are renowned as one of the most spectacular examples of adaptive radiation. They provide a unique opportunity to investigate the relationships between ecology, morphological diversity, and phylogeny in producing such remarkable diversity. Nevertheless, the parameters of the adaptive radiations of these fish have not been satisfactorily quantified yet. Lake Tanganyika possesses all of the major lineages of East African cichlid fish, so by using geometric morphometrics and comparative analyses of ecology and morphology, in an explicitly phylogenetic context, we quantify the role of ecology in driving adaptive speciation. We used geometric morphometric methods to describe the body shape of over 1000 specimens of East African cichlid fish, with a focus on the Lake Tanganyika species assemblage, which is composed of more than 200 endemic species. The main differences in shape concern the length of the whole body and the relative sizes of the head and caudal peduncle. We investigated the influence of phylogeny on similarity of shape using both distance-based and variance partitioning methods, finding that phylogenetic inertia exerts little influence on overall body shape. Therefore, we quantified the relative effect of major ecological traits on shape using phylogenetic generalized least squares and disparity analyses. These analyses conclude that body shape is most strongly predicted by feeding preferences (i.e., trophic niches) and the water depths at which species occur. Furthermore, the morphological disparity within tribes indicates that even though the morphological diversification associated with explosive speciation has happened in only a few tribes of the Tanganyikan assemblage, the potential to evolve diverse morphologies exists in all tribes. Quantitative data support the existence of extensive parallelism in several independent adaptive radiations in Lake Tanganyika. Notably, Tanganyikan mouthbrooders belonging to the C-lineage and the substrate spawning Lamprologini have evolved a multitude of different shapes from elongated and Lamprologus-like hypothetical ancestors. Together, these data demonstrate strong support for the adaptive character of East African cichlid radiations.
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The class of Schoenberg transformations, embedding Euclidean distances into higher dimensional Euclidean spaces, is presented, and derived from theorems on positive definite and conditionally negative definite matrices. Original results on the arc lengths, angles and curvature of the transformations are proposed, and visualized on artificial data sets by classical multidimensional scaling. A distance-based discriminant algorithm and a robust multidimensional centroid estimate illustrate the theory, closely connected to the Gaussian kernels of Machine Learning.
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Avalanche forecasting is a complex process involving the assimilation of multiple data sources to make predictions over varying spatial and temporal resolutions. Numerically assisted forecasting often uses nearest neighbour methods (NN), which are known to have limitations when dealing with high dimensional data. We apply Support Vector Machines to a dataset from Lochaber, Scotland to assess their applicability in avalanche forecasting. Support Vector Machines (SVMs) belong to a family of theoretically based techniques from machine learning and are designed to deal with high dimensional data. Initial experiments showed that SVMs gave results which were comparable with NN for categorical and probabilistic forecasts. Experiments utilising the ability of SVMs to deal with high dimensionality in producing a spatial forecast show promise, but require further work.
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Breathing-induced bulk motion of the myocardium during data acquisition may cause severe image artifacts in coronary magnetic resonance angiography (MRA). Current motion compensation strategies include breath-holding or free-breathing MR navigator gating and tracking techniques. Navigator-based techniques have been further refined by the applications of sophisticated 2D k-space reordering techniques. A further improvement in image quality and a reduction of relative scanning duration may be expected from a 3D k-space reordering scheme. Therefore, a 3D k-space reordered acquisition scheme including a 3D navigator gated and corrected segmented k-space gradient echo imaging sequence for coronary MRA was implemented. This new zonal motion-adapted acquisition and reordering technique (ZMART) was developed on the basis of a numerical simulation of the Bloch equations. The technique was implemented on a commercial 1.5T MR system, and first phantom and in vivo experiments were performed. Consistent with the results of the theoretical findings, the results obtained in the phantom studies demonstrate a significant reduction of motion artifacts when compared to conventional (non-k-space reordered) gating techniques. Preliminary in vivo findings also compare favorably with the phantom experiments and theoretical considerations. Magn Reson Med 45:645-652, 2001.
Resumo:
Résumé La protéomique basée sur la spectrométrie de masse est l'étude du proteome l'ensemble des protéines exprimées au sein d'une cellule, d'un tissu ou d'un organisme - par cette technique. Les protéines sont coupées à l'aide d'enzymes en plus petits morceaux -les peptides -, et, séparées par différentes techniques. Les différentes fractions contenant quelques centaines de peptides sont ensuite analysées dans un spectromètre de masse. La masse des peptides est enregistrée et chaque peptide est séquentiellement fragmenté pour en obtenir sa séquence. L'information de masse et séquence est ensuite comparée à une base de données de protéines afin d'identifier la protéine d'origine. Dans une première partie, la thèse décrit le développement de méthodes d'identification. Elle montre l'importance de l'enrichissement de protéines comme moyen d'accès à des protéines de moyenne à faible abondance dans le lait humain. Elle utilise des injections répétées pour augmenter la couverture en protéines et la confiance dans l'identification. L'impacte de nouvelle version de base de données sur la liste des protéines identifiées est aussi démontré. De plus, elle utilise avec succès la spectrométrie de masse comme alternative aux anticorps, pour valider la présence de 34 constructions de protéines pathogéniques du staphylocoque doré exprimées dans une souche de lactocoque. Dans une deuxième partie, la thèse décrit le développement de méthodes de quantification. Elle expose de nouvelles approches de marquage des terminus des protéines aux isotopes stables et décrit la première méthode de marquage des groupements carboxyliques au niveau protéine à l'aide de réactifs composé de carbone 13. De plus, une nouvelle méthode, appelée ANIBAL, marquant tous les groupements amines et carboxyliques au niveau de la protéine, est exposée. Summary Mass spectrometry-based proteomics is the study of the proteome -the set of all expressed proteins in a cell, tissue or organism -using mass spectrometry. Proteins are cut into smaller pieces - peptides - using proteolytic enzymes and separated using different separation techniques. The different fractions containing several hundreds of peptides are than analyzed by mass spectrometry. The mass of the peptides entering the instrument are recorded and each peptide is sequentially fragmented to obtain its amino acid sequence. Each peptide sequence with its corresponding mass is then searched against a protein database to identify the protein to which it belongs. This thesis presents new method developments in this field. In a first part, the thesis describes development of identification methods. It shows the importance of protein enrichment methods to gain access to medium-to-low abundant proteins in a human milk sample. It uses repeated injection to increase protein coverage and confidence in identification and demonstrates the impact of new database releases on protein identification lists. In addition, it successfully uses mass spectrometry as an alternative to antibody-based assays to validate the presence of 34 different recombinant constructs of Staphylococcus aureus pathogenic proteins expressed in a Lactococcus lactis strain. In a second part, development of quantification methods is described. It shows new stable isotope labeling approaches based on N- and C-terminus labeling of proteins and describes the first method of labeling of carboxylic groups at the protein level using 13C stable isotopes. In addition, a new quantitative approach called ANIBAL is explained that labels all amino and carboxylic groups at the protein level.
Resumo:
Introduction: Difficult tracheal intubation remains a constant and significant source of morbidity and mortality in anaesthetic practice. Insufficient airway assessment in the preoperative period continues to be a major cause of unanticipated difficult intubation. Although many risk factors have already been identified, preoperative airway evaluation is not always regarded as a standard procedure and the respective weight of each risk factor remains unclear. Moreover the predictive scores available are not sensitive, moderately specific and often operator-dependant. In order to improve the preoperative detection of patients at risk for difficult intubation, we developed a system for automated and objective evaluation of morphologic criteria of the face and neck using video recordings and advanced techniques borrowed from face recognition. Method and results: Frontal video sequences were recorded in 5 healthy volunteers. During the video recording, subjects were requested to perform maximal flexion-extension of the neck and to open wide the mouth with tongue pulled out. A robust and real-time face tracking system was then applied, allowing to automatically identify and map a grid of 55 control points on the face, which were tracked during head motion. These points located important features of the face, such as the eyebrows, the nose, the contours of the eyes and mouth, and the external contours, including the chin. Moreover, based on this face tracking, the orientation of the head could also be estimated at each frame of the video sequence. Thus, we could infer for each frame the pitch angle of the head pose (related to the vertical rotation of the head) and obtain the degree of head extension. Morphological criteria used in the most frequent cited predictive scores were also extracted, such as mouth opening, degree of visibility of the uvula or thyreo-mental distance. Discussion and conclusion: Preliminary results suggest the high feasibility of the technique. The next step will be the application of the same automated and objective evaluation to patients who will undergo tracheal intubation. The difficulties related to intubation will be then correlated to the biometric characteristics of the patients. The objective in mind is to analyze the biometrics data with artificial intelligence algorithms to build a highly sensitive and specific predictive test.
Resumo:
Introduction: Ankle arthrodesis (AD) and total ankle replacement (TAR) are typical treatments for ankle osteoarthritis (AO). Despite clinical interest, there is a lack of their outcome evaluation using objective criteria. Gait analysis and plantar pressure assessment are appropriate to detect pathologies in orthopaedics but they are mostly used in lab with few gait cycles. In this study, we propose an ambulatory device based on inertial and plantar pressure sensors to compare the gait during long-distance trials between healthy subjects (H) and patients with AO or treated by AD and TAR. Methods: Our study included four groups: 11 patients with AO, 9 treated by TAR, 7 treated by AD and 6 control subjects. An ambulatory system (Physilog®, CH) was used for gait analysis; plantar pressure measurements were done using a portable insole (Pedar®-X, DE). The subjects were asked to walk 50 meters in two trials. Mean value and coefficient of variation of spatio-temporal gait parameters were calculated for each trial. Pressure distribution was analyzed in ten subregions of foot. All parameters were compared among the four groups using multi-level model-based statistical analysis. Results: Significant difference (p <0.05) with control was noticed for AO patients in maximum force in medial hindfoot and forefoot and in central forefoot. These differences were no longer significant in TAR and AD groups. Cadence and speed of all pathologic groups showed significant difference with control. Both treatments showed a significant improvement in double support and stance. TAR decreased variability in speed, stride length and knee ROM. Conclusions: In spite of a small sample size, this study showed that ankle function after AO treatments can be evaluated objectively based on plantar pressure and spatio-temporal gait parameters measured during unconstrained walking outside the lab. The combination of these two ambulatory techniques provides a promising way to evaluate foot function in clinics.