Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

Assessment of Severe Apnoea through Voice Analysis, Automatic Speech, and Speaker Recognition Techniques

This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based detection could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we describe an acoustic search for distinctive apnoea voice characteristics. We also study abnormal nasalization in OSA patients by modelling vowels in nasal and nonnasal phonetic contexts using Gaussian Mixture Model (GMM) pattern recognition on speech spectra. Finally, we present experimental findings regarding the discriminative power of GMMs applied to severe apnoea detection. We have achieved an 81% correct classification rate, which is very promising and underpins the interest in this line of inquiry.

Adipose tissue gene expression of factors related to lipid processing in obesity.

BACKGROUND Adipose tissue lipid storage and processing capacity can be a key factor for obesity-related metabolic disorders such as insulin resistance and diabetes. Lipid uptake is the first step to adipose tissue lipid storage. The aim of this study was to analyze the gene expression of factors involved in lipid uptake and processing in subcutaneous (SAT) and visceral (VAT) adipose tissue according to body mass index (BMI) and the degree of insulin resistance (IR). METHODS AND PRINCIPAL FINDINGS VLDL receptor (VLDLR), lipoprotein lipase (LPL), acylation stimulating protein (ASP), LDL receptor-related protein 1 (LRP1) and fatty acid binding protein 4 (FABP4) gene expression was measured in VAT and SAT from 28 morbidly obese patients with Type 2 Diabetes Mellitus (T2DM) or high IR, 10 morbidly obese patients with low IR, 10 obese patients with low IR and 12 lean healthy controls. LPL, FABP4, LRP1 and ASP expression in VAT was higher in lean controls. In SAT, LPL and FABP4 expression were also higher in lean controls. BMI, plasma insulin levels and HOMA-IR correlated negatively with LPL expression in both VAT and SAT as well as with FABP4 expression in VAT. FABP4 gene expression in SAT correlated inversely with BMI and HOMA-IR. However, multiple regression analysis showed that BMI was the main variable contributing to LPL and FABP4 gene expression in both VAT and SAT. CONCLUSIONS Morbidly obese patients have a lower gene expression of factors related with lipid uptake and processing in comparison with healthy lean persons.

Digital beamforming and moving target indication for future spaceborne synthetic aperture radar

During the last decade the interest on space-borne Synthetic Aperture Radars (SAR) for remote sensing applications has grown as testified by the number of recent and forthcoming missions as TerraSAR-X, RADARSAT-2, COSMO-kyMed, TanDEM-X and the Spanish SEOSAR/PAZ. In this sense, this thesis proposes to study and analyze the performance of the state-of-the-Art space-borne SAR systems, with modes able to provide Moving Target Indication capabilities (MTI), i.e. moving object detection and estimation. The research will focus on the MTI processing techniques as well as the architecture and/ or configuration of the SAR instrument, setting the limitations of the current systems with MTI capabilities, and proposing efficient solutions for the future missions. Two European projects, to which the Universitat Politècnica de Catalunya provides support, are an excellent framework for the research activities suggested in this thesis. NEWA project proposes a potential European space-borne radar system with MTI capabilities in order to fulfill the upcoming European security policies. This thesis will critically review the state-of-the-Art MTI processing techniques as well as the readiness and maturity level of the developed capabilities. For each one of the techniques a performance analysis will be carried out based on the available technologies, deriving a roadmap and identifying the different technological gaps. In line with this study a simulator tool will be developed in order to validate and evaluate different MTI techniques in the basis of a flexible space-borne radar configuration. The calibration of a SAR system is mandatory for the accurate formation of the SAR images and turns to be critical in the advanced operation modes as MTI. In this sense, the SEOSAR/PAZ project proposes the study and estimation of the radiometric budget. This thesis will also focus on an exhaustive analysis of the radiometric budget considering the current calibration concepts and their possible limitations. In the framework of this project a key point will be the study of the Dual Receive Antenna (DRA) mode, which provides MTI capabilities to the mission. An additional aspect under study is the applicability of the Digital Beamforming on multichannel and/or multistatic radar platforms, which conform potential solutions for the NEWA project with the aim to fully exploit its capability jointly with MTI techniques.

Automatic landmarks detection in breast reconstruction aesthetic assessment.

This paper addresses a fully automatic landmarks detection method for breast reconstruction aesthetic assessment. The set of landmarks detected are the supraesternal notch (SSN), armpits, nipples, and inframammary fold (IMF). These landmarks are commonly used in order to perform anthropometric measurements for aesthetic assessment. The methodological approach is based on both illumination and morphological analysis. The proposed method has been tested with 21 images. A good overall performance is observed, although several improvements must be achieved in order to refine the detection of nipples and SSNs.

Imagerie cardiaque non invasive: apport spécifique en clinique des nouvelles modalités (I). Evaluation morphologique [Cardiac imaging: specific clinical role of newly developed non invasive techniques. Part 1: Morphological evaluation].

Echocardiography is the preferred initial test to assess cardiac morphology and ventricular function. Cardiac MRI enables an optimal visualisation of heart muscle without contrast injection, and precise measurement of the ventricular volumes and systolic function. It is therefore an ideal test for patients with poor echocardiographic windows or for the specific evaluation of right heart chambers. Heart CT also remarkably images heart muscle and precisely measures ventricular systolic function after intravenous injection of iodinated contrast. Coronary CT may also, in selected cases, avoid the need for diagnostic coronary angiography. Although very accurate, these imaging modalities are expensive and may be contra-indicated for a particular patient. Their use in clinical practice has to follow the accepted guidelines.

Object and Scene Classification: what does a Supervised Approach Provide us?

Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurrences to perform a scene classification (e.g. beach scene, mountain scene). We achieve this by using a supervised learning algorithm able to learn with few images to facilitate the user task. We use a probabilistic model to recognise the objects and further we classify the scene based on their object occurrences. Experimental results are shown and evaluated to prove the validity of our proposal. Object recognition performance is compared to the approaches of He et al. (2004) and Marti et al. (2001) using their own datasets. Furthermore an unsupervised method is implemented in order to evaluate the advantages and disadvantages of our supervised classification approach versus an unsupervised one

Kernel-based methods for change detection in remote sensing images

Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.

A 2D/3D image analysis system to track fluorescently labeled structures in rod-shaped cells: application to measure spindle pole asymmetry during mitosis.

BACKGROUND: The yeast Schizosaccharomyces pombe is frequently used as a model for studying the cell cycle. The cells are rod-shaped and divide by medial fission. The process of cell division, or cytokinesis, is controlled by a network of signaling proteins called the Septation Initiation Network (SIN); SIN proteins associate with the SPBs during nuclear division (mitosis). Some SIN proteins associate with both SPBs early in mitosis, and then display strongly asymmetric signal intensity at the SPBs in late mitosis, just before cytokinesis. This asymmetry is thought to be important for correct regulation of SIN signaling, and coordination of cytokinesis and mitosis. In order to study the dynamics of organelles or large protein complexes such as the spindle pole body (SPB), which have been labeled with a fluorescent protein tag in living cells, a number of the image analysis problems must be solved; the cell outline must be detected automatically, and the position and signal intensity associated with the structures of interest within the cell must be determined. RESULTS: We present a new 2D and 3D image analysis system that permits versatile and robust analysis of motile, fluorescently labeled structures in rod-shaped cells. We have designed an image analysis system that we have implemented as a user-friendly software package allowing the fast and robust image-analysis of large numbers of rod-shaped cells. We have developed new robust algorithms, which we combined with existing methodologies to facilitate fast and accurate analysis. Our software permits the detection and segmentation of rod-shaped cells in either static or dynamic (i.e. time lapse) multi-channel images. It enables tracking of two structures (for example SPBs) in two different image channels. For 2D or 3D static images, the locations of the structures are identified, and then intensity values are extracted together with several quantitative parameters, such as length, width, cell orientation, background fluorescence and the distance between the structures of interest. Furthermore, two kinds of kymographs of the tracked structures can be established, one representing the migration with respect to their relative position, the other representing their individual trajectories inside the cell. This software package, called "RodCellJ", allowed us to analyze a large number of S. pombe cells to understand the rules that govern SIN protein asymmetry. CONCLUSIONS: "RodCell" is freely available to the community as a package of several ImageJ plugins to simultaneously analyze the behavior of a large number of rod-shaped cells in an extensive manner. The integration of different image-processing techniques in a single package, as well as the development of novel algorithms does not only allow to speed up the analysis with respect to the usage of existing tools, but also accounts for higher accuracy. Its utility was demonstrated on both 2D and 3D static and dynamic images to study the septation initiation network of the yeast Schizosaccharomyces pombe. More generally, it can be used in any kind of biological context where fluorescent-protein labeled structures need to be analyzed in rod-shaped cells. AVAILABILITY: RodCellJ is freely available under http://bigwww.epfl.ch/algorithms.html, (after acceptance of the publication).

Atlas-based segmentation of pathological brain MR images

We propose a method for brain atlas deformation inpresence of large space-occupying tumors, based on an apriori model of lesion growth that assumes radialexpansion of the lesion from its starting point. First,an affine registration brings the atlas and the patientinto global correspondence. Then, the seeding of asynthetic tumor into the brain atlas provides a templatefor the lesion. Finally, the seeded atlas is deformed,combining a method derived from optical flow principlesand a model of lesion growth (MLG). Results show that themethod can be applied to the automatic segmentation ofstructures and substructures in brains with grossdeformation, with important medical applications inneurosurgery, radiosurgery and radiotherapy.

Analysis and evaluation of techniques for the extraction of classes in the ontology learning process

This paper analyzes and evaluates, in the context of Ontology learning, some techniques to identify and extract candidate terms to classes of a taxonomy. Besides, this work points out some inconsistencies that may be occurring in the preprocessing of text corpus, and proposes techniques to obtain good terms candidate to classes of a taxonomy.

Wall motion estimation in intracranial aneurysms

The quantification of wall motion in cerebral aneurysms is becoming important owing to its potential connection to rupture, and as a way to incorporate the effects of vascular compliance in computational fluid dynamics (CFD) simulations.Most of papers report values obtained with experimental phantoms, simulated images, or animal models, but the information for real patients is limited. In this paper, we have combined non-rigid registration (IR) with signal processing techniques to measure pulsation in real patients from high frame rate digital subtraction angiography (DSA). We have obtained physiological meaningful waveforms with amplitudes in therange 0mm-0.3mm for a population of 18 patients including ruptured and unruptured aneurysms. Statistically significant differences in pulsation were found according to the rupture status, in agreement with differences in biomechanical properties reported in the literature.

Contrast agent-enhanced, free-breathing, three-dimensional coronary magnetic resonance angiography.

For free-breathing, high-resolution, three-dimensional coronary magnetic resonance angiography (MRA), the use of intravascular contrast agents may be helpful for contrast enhancement between coronary blood and myocardium. In six patients, 0.1 mmol/kg of the intravascular contrast agent MS-325/AngioMARK was given intravenously followed by double-oblique, free-breathing, three-dimensional inversion-recovery coronary MRA with real-time navigator gating and motion correction. Contrast-enhanced, three-dimensional coronary MRA images were compared with images obtained with a T2 prepulse (T2Prep) without exogenous contrast. The contrast-enhanced images demonstrated a 69% improvement in the contrast-to-noise ratio (6.6 +/- 1.1 vs. 11.1 +/- 2.5; P < 0.01) compared with the T2Prep approach. By using the intravascular agent, extensive portions (> 80 mm) of the native left and right coronary system could be displayed consistently with sub-millimeter in-plane resolution. The intravascular contrast agent, MS-325/AngioMARK, leads to a considerable enhancement of the blood/muscle contrast for coronary MRA compared with T2Prep techniques. The clinical value of the agent remains to be defined in a larger patient series. J. Magn. Reson. Imaging 1999;10:790-799.

Proverbes, dictons et expressions imagées dans l’enseignement/apprentissage du FLE, dans le secondaire au Cap-Vert.

Pour bien maîtriser une langue, il faut sans doute en avoir une connaissance la plus large possible, ce qui demande alors l’enseignement/apprentissage de tous les éléments qui la composent. Dans ce cas, il est très important de savoir quels sont, parmi ces éléments, ceux qui sont amenés en classe et comment ils y sont présentés. Il y en a certains qui ne fi-gurent pas dans le programme destiné à l’enseignement/apprentissage de la langue fran-çaise. S’ils l’étaient, probablement ils seraient enseignés. Mais, d’après notre constat, non seulement ils ne figurent pas, comme ils ne sont pas ou presque pas traités en cours par l’initiative des professeurs, bien qu’ils soient parmi les éléments les plus importants dans l’apprentissage d’une langue. Très souvent, ce sont ces éléments qui sont à la base de la motivation pour l’apprentissage des langues puisqu’ils constituent, d’une certaine manière, le charme et la beauté d’une langue. Nous en avons pris trois (proverbe, dicton et expres-sion imagée), qui peuvent représenter la manière de vivre ; de penser ; la culture, les cou-tumes et les habitudes d’un peuple. Il faut préciser que ce constat nous l’avons fait depuis longtemps. Par conséquent, nous avons décidé de traduire l’inquiétude que cette problématique provoque chez nous en ce travail de recherche qui a été mené sous le thème de : Proverbes, dictons et expres-sions imagées dans l’enseignement/apprentissage du FLE, dans le secondaire au Cap- Vert. Dans l’ensemble, ce travail est composé de trois parties. Dans la première partie, après les consultations de documents, nous avons proposé une réflexion sur le proverbe, le dicton et l’expression imagée en ce qui concerne leur origine et leur contexte social, temporel, leur durée, et leur situation actuelle par rapport à leur utilisation ou leur étude. Nous en avons également présenté quelques définitions, en insistant sur la distinction entre les mêmes, vu que pendant les recherches, nous avons constaté qu’il y a parfois, une confusion entre eux. Puis, dans la deuxième partie, à travers des enquêtes qui ont été menées sur le terrain dans quelques lycées de Praia, nous avons présenté sous forme d’analyse, la situation ac-tuelle concernant le recours aux proverbes, dictons et expressions imagées par le professeur dans ses cours, bien comme l’intérêt et la motivation des élèves face aux mêmes. Finalement, dans la troisième et dernière partie, nous avons dressé une liste composée de proverbes, dictons et expressions imagées que nous avons fait accompagner de leur pays d’origine, quand cela a été possible. Ils ont été analysés et nous avons essayé de montrer également, l’utilité pratique de leur message, soit pour les élèves à l’école, soit d’une ma-nière plus générale, pour toute la vie dans la société. Pour donner un caractère pratique à notre travail, nous avons fait quelques proposi-tions de techniques d’exploitation de proverbes, dictons et expressions imagées, dans les classes. C’est-à-dire, nous avons essayé d’apporter des suggestions qui peuvent être appli-quées à un éventuel engagement de la part des professeurs ou d’autres intervenants concer-nés à la résolution de la problématique qui a légitimé notre recherche.