Harmonic active contours.

We propose a segmentation method based on the geometric representation of images as 2-D manifolds embedded in a higher dimensional space. The segmentation is formulated as a minimization problem, where the contours are described by a level set function and the objective functional corresponds to the surface of the image manifold. In this geometric framework, both data-fidelity and regularity terms of the segmentation are represented by a single functional that intrinsically aligns the gradients of the level set function with the gradients of the image and results in a segmentation criterion that exploits the directional information of image gradients to overcome image inhomogeneities and fragmented contours. The proposed formulation combines this robust alignment of gradients with attractive properties of previous methods developed in the same geometric framework: 1) the natural coupling of image channels proposed for anisotropic diffusion and 2) the ability of subjective surfaces to detect weak edges and close fragmented boundaries. The potential of such a geometric approach lies in the general definition of Riemannian manifolds, which naturally generalizes existing segmentation methods (the geodesic active contours, the active contours without edges, and the robust edge integrator) to higher dimensional spaces, non-flat images, and feature spaces. Our experiments show that the proposed technique improves the segmentation of multi-channel images, images subject to inhomogeneities, and images characterized by geometric structures like ridges or valleys.

Dense Deformation Field Estimation for Atlas Registration using the Active Contour Framework

In this paper, we propose a new paradigm to carry outthe registration task with a dense deformation fieldderived from the optical flow model and the activecontour method. The proposed framework merges differenttasks such as segmentation, regularization, incorporationof prior knowledge and registration into a singleframework. The active contour model is at the core of ourframework even if it is used in a different way than thestandard approaches. Indeed, active contours are awell-known technique for image segmentation. Thistechnique consists in finding the curve which minimizesan energy functional designed to be minimal when thecurve has reached the object contours. That way, we getaccurate and smooth segmentation results. So far, theactive contour model has been used to segment objectslying in images from boundary-based, region-based orshape-based information. Our registration technique willprofit of all these families of active contours todetermine a dense deformation field defined on the wholeimage. A well-suited application of our model is theatlas registration in medical imaging which consists inautomatically delineating anatomical structures. Wepresent results on 2D synthetic images to show theperformances of our non rigid deformation field based ona natural registration term. We also present registrationresults on real 3D medical data with a large spaceoccupying tumor substantially deforming surroundingstructures, which constitutes a high challenging problem.

Permanent demand excess as business strategy: an analysis of the Brazilian higher-education market

Many Higher Education Institutions (HEIs) establish tuition below the equilibrium price to generate permanent demand excess. This paper first adapts Becker’s (1991) theory to understand why the HEIs price in this way. The fact that students are both consumers and inputs on the education production process gives rise to a market equilibrium where some firms have excess demand and charge high prices, and others charge low prices and have empty seats.Second, the paper analyzes this equilibrium empirically. We estimated the demand for undergraduate courses in Business Administration in the State of São Paulo. The results show that tuition, quality of incoming students and percentage of lecturers holding doctorates degrees are the determining factors of students’ choice. Since the student quality determines the demand for a HEI, it is calculated what the value is for a HEI to get better students; that is the total revenue that each HEI gives up to guarantee excess demand. Regarding the “investment” in selectivity, 39 HEIs in São Paulo give up a combined R$ 5 million (or US$ 3.14 million) in revenue per year per freshman class, which means 7.6% of the revenue coming from a freshman class.

The Molecular Basis for Antimicrobial Activity of Pore-Forming Cyclic Peptides

The mechanism of action of antimicrobial peptides is, to our knowledge, still poorly understood. To probe the biophysical characteristics that confer activity, we present here a molecular-dynamics and biophysical study of a cyclic antimicrobial peptide and its inactive linear analog. In the simulations, the cyclic peptide caused large perturbations in the bilayer and cooperatively opened a disordered toroidal pore, 1–2 nm in diameter. Electrophysiology measurements confirm discrete poration events of comparable size. We also show that lysine residues aligning parallel to each other in the cyclic but not linear peptide are crucial for function. By employing dual-color fluorescence burst analysis, we show that both peptides are able to fuse/aggregate liposomes but only the cyclic peptide is able to porate them. The results provide detailed insight on the molecular basis of activity of cyclic antimicrobial peptides

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment

Assessment of particulate exposure and surface characteristics in association with urinary levels of 8-hydroxy-2'-deoxyguanosine, considered as marker of oxidative stress

Epidemiological studies have demonstrated that exposure to fine particles is associated to adverse health effects, including cancer, respiratory and cardiovascular diseases. However, mechanisms by which particles induce health effects remain unclear. According to one of the most investigated hypotheses, particles cause adverse effects through the production of reactive oxygen species (ROS), which are very hazardous compounds able to attack directly biological structures, including the DNA strand or the lipid bilayer of the cells. If the defense mechanisms, constituted of antioxidants, are not able to counter ROS, then these compounds will cause in the body a range of oxidation reactions called "oxidative stress". The aim of the present research project was to better understand mechanisms by which exposure to fine particles induces oxidative stress. The first point of this project was to check whether exposure to high levels of fine particles is directly linked to oxidative stress, and whether this oxidative stress is accompanied by the activation of the defense mechanisms (antioxidants). The second point was to study the role played by the particle surface characteristics in the oxidative stress process. For that purpose, a study was conducted in bus depots with the participation of 40 mechanics. First, occupational exposure to particles (PM4) and to other pollutants (NOx, O3) was measured over a two-day period. Then, urine samples of mechanics were collected in order to measure levels of 8-hydroxy-2'-deoxyguanosine (8OHdG) and antioxidants. 8OHdG is a molecule formed by the oxidation of DNA and allowing to assess the oxidative stress status of the mechanics. Finally, particles were collected on filters, and functional groups located on the particle surface were analyzed in the laboratory using a Knudsen flow reactor. This technique allows not only to quantify functional groups on the particle surface, but also to measure the reaction kinetics. Results obtained during the field campaign in bus depots showed that mechanics were exposed to rather low levels of PM4 (20-85 μg/m3) and of pollutants (NOx: 100-1000 ppb; O3: <15 ppb). However, despite this low exposure, urinary levels of the oxidative stress biomarker (8OHdG) increased significantly for non-smoking workers over a two-day period of shift. This oxidative stress was accompanied by an increase of antioxidants, indicating the activation of defense mechanisms. On the other hand, the analysis of functional groups on the particle surface showed important differences, depending on the workplace, the date and the activities of workers. The particle surface contained simultaneously antagonistic functional groups which did not undergo internal reactions (such as acids and bases), and was usually characterized by a high density of carbonyl functions and a low density of acidic sites. Reaction kinetics measured using the Knudsen flow reactor pointed out fast reactions of oxidizable groups and slow reactions of acidic sites. Several exposure parameters were significantly correlated with the increase of the oxidative stress status: the presence of acidic sites, carbonyl functions and oxidizable groups on the particle surface; reaction kinetics of functional groups on the particle surface; particulate iron and copper concentrations; and NOx concentration.

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).

Temporal SNR characteristics in segmented 3D-EPI at 7T.

Three-dimensional segmented echo planar imaging (3D-EPI) is a promising approach for high-resolution functional magnetic resonance imaging, as it provides an increased signal-to-noise ratio (SNR) at similar temporal resolution to traditional multislice 2D-EPI readouts. Recently, the 3D-EPI technique has become more frequently used and it is important to better understand its implications for fMRI. In this study, the temporal SNR characteristics of 3D-EPI with varying numbers of segments are studied. It is shown that, in humans, the temporal variance increases with the number of segments used to form the EPI acquisition and that for segmented acquisitions, the maximum available temporal SNR is reduced compared to single shot acquisitions. This reduction with increased segmentation is not found in phantom data and thus likely due to physiological processes. When operating in the thermal noise dominated regime, fMRI experiments with a motor task revealed that the 3D variant outperforms the 2D-EPI in terms of temporal SNR and sensitivity to detect activated brain regions. Thus, the theoretical SNR advantage of a segmented 3D-EPI sequence for fMRI only exists in a low SNR situation. However, other advantages of 3D-EPI, such as the application of parallel imaging techniques in two dimensions and the low specific absorption rate requirements, may encourage the use of the 3D-EPI sequence for fMRI in situations with higher SNR.

Right coronary artery flow velocity and volume assessment with spiral K-space sampled breathhold velocity-encoded MRI at 3 tesla: accuracy and reproducibility.

PURPOSE: To evaluate accuracy and reproducibility of flow velocity and volume measurements in a phantom and in human coronary arteries using breathhold velocity-encoded (VE) MRI with spiral k-space sampling at 3 Tesla. MATERIALS AND METHODS: Flow velocity assessment was performed using VE MRI with spiral k-space sampling. Accuracy of VE MRI was tested in vitro at five constant flow rates. Reproducibility was investigated in 19 healthy subjects (mean age 25.4 +/- 1.2 years, 11 men) by repeated acquisition in the right coronary artery (RCA). RESULTS: MRI-measured flow rates correlated strongly with volumetric collection (Pearson correlation r = 0.99; P < 0.01). Due to limited sample resolution, VE MRI overestimated the flow rate by 47% on average when nonconstricted region-of-interest segmentation was used. Using constricted region-of-interest segmentation with lumen size equal to ground-truth luminal size, less than 13% error in flow rate was found. In vivo RCA flow velocity assessment was successful in 82% of the applied studies. High interscan, intra- and inter-observer agreement was found for almost all indices describing coronary flow velocity. Reproducibility for repeated acquisitions varied by less than 16% for peak velocity values and by less than 24% for flow volumes. CONCLUSION: 3T breathhold VE MRI with spiral k-space sampling enables accurate and reproducible assessment of RCA flow velocity.

Toward integrated management of cerebral aneurysms

In the last few years, some of the visionary concepts behind the virtual physiological human began to be demonstrated on various clinical domains, showing great promise for improving healthcare management. In the current work, we provide an overview of image- and biomechanics-based techniques that, when put together, provide a patient-specific pipeline for the management of intracranial aneurysms. The derivation and subsequent integration of morphological, morphodynamic, haemodynamic and structural analyses allow us to extract patient-specific models and information from which diagnostic and prognostic descriptors can be obtained. Linking such new indices with relevant clinical events should bring new insights into the processes behind aneurysm genesis, growth and rupture. The development of techniques for modelling endovascular devices such as stents and coils allows the evaluation of alternative treatment scenarios before the intervention takes place and could also contribute to the understanding and improved design of more effective devices. A key element to facilitate the clinical take-up of all these developments is their comprehensive validation. Although a number of previously published results have shown the accuracy and robustness of individual components, further efforts should be directed to demonstrate the diagnostic and prognostic efficacy of these advanced tools through large-scale clinical trials.

Automatic low baseline stereo in urban areas

In this work we propose a new automatic methodology for computing accurate digital elevation models (DEMs) in urban environments from low baseline stereo pairs that shall be available in the future from a new kind of earth observation satellite. This setting makes both views of the scene similarly, thus avoiding occlusions and illumination changes, which are the main disadvantages of the commonly accepted large-baseline configuration. There still remain two crucial technological challenges: (i) precisely estimating DEMs with strong discontinuities and (ii) providing a statistically proven result, automatically. The first one is solved here by a piecewise affine representation that is well adapted to man-made landscapes, whereas the application of computational Gestalt theory introduces reliability and automation. In fact this theory allows us to reduce the number of parameters to be adjusted, and tocontrol the number of false detections. This leads to the selection of a suitable segmentation into affine regions (whenever possible) by a novel and completely automatic perceptual grouping method. It also allows us to discriminate e.g. vegetation-dominated regions, where such an affine model does not apply anda more classical correlation technique should be preferred. In addition we propose here an extension of the classical ”quantized” Gestalt theory to continuous measurements, thus combining its reliability with the precision of variational robust estimation and fine interpolation methods that are necessary in the low baseline case. Such an extension is very general and will be useful for many other applications as well.

Magnetization transfer-based 3D visualization of foot peripheral nerves.

PURPOSE: To investigate magnetization transfer (MT) effects as a new source of contrast for imaging and tracking of peripheral foot nerves. MATERIALS AND METHODS: Two sets of 3D spoiled gradient-echo images acquired with and without a saturation pulse were used to generate MT ratio (MTR) maps of 260 μm in-plane resolution for eight volunteers at 3T. Scan parameters were adjusted to minimize signal loss due to T2 dephasing, and a dedicated coil was used to improve the inherently low signal-to-noise ratio of small voxels. Resulting MTR values in foot nerves were compared with those in surrounding muscle tissue. RESULTS: Average MTR values for muscle (45.5 ± 1.4%) and nerve (21.4 ± 3.1%) were significantly different (P < 0.0001). In general, the difference in MTR values was sufficiently large to allow for intensity-based segmentation and tracking of foot nerves in individual subjects. This procedure was termed MT-based 3D visualization. CONCLUSION: The MTR serves as a new source of contrast for imaging of peripheral foot nerves and provides a means for high spatial resolution tracking of these structures. The proposed methodology is directly applicable on standard clinical MR scanners and could be applied to systemic pathologies, such as diabetes.

Predicting clinical scores from magnetic resonance scans in Alzheimer's disease.

Machine learning and pattern recognition methods have been used to diagnose Alzheimer's disease (AD) and mild cognitive impairment (MCI) from individual MRI scans. Another application of such methods is to predict clinical scores from individual scans. Using relevance vector regression (RVR), we predicted individuals' performances on established tests from their MRI T1 weighted image in two independent data sets. From Mayo Clinic, 73 probable AD patients and 91 cognitively normal (CN) controls completed the Mini-Mental State Examination (MMSE), Dementia Rating Scale (DRS), and Auditory Verbal Learning Test (AVLT) within 3months of their scan. Baseline MRI's from the Alzheimer's disease Neuroimaging Initiative (ADNI) comprised the other data set; 113 AD, 351 MCI, and 122 CN subjects completed the MMSE and Alzheimer's Disease Assessment Scale-Cognitive subtest (ADAS-cog) and 39 AD, 92 MCI, and 32 CN ADNI subjects completed MMSE, ADAS-cog, and AVLT. Predicted and actual clinical scores were highly correlated for the MMSE, DRS, and ADAS-cog tests (P<0.0001). Training with one data set and testing with another demonstrated stability between data sets. DRS, MMSE, and ADAS-Cog correlated better than AVLT with whole brain grey matter changes associated with AD. This result underscores their utility for screening and tracking disease. RVR offers a novel way to measure interactions between structural changes and neuropsychological tests beyond that of univariate methods. In clinical practice, we envision using RVR to aid in diagnosis and predict clinical outcome.

Temporary employment in advanced economies: drawing lessons from Spain

This study analyses the determinants of the rate of temporary employment in various OECD countries using both macro-level data drawn from the OECD and EUROSTAT databases, as well as micro-level data drawn from the 8th wave of the European Household Panel. Comparative analysis is set out to test different explanations originally formulated for the Spanish case. The evidence suggests that the overall distribution of temporary employment in advanced economies does not seem to be explicable by the characteristics of national productive structures. This evidence seems at odds with previous interpretations based on segmentation theories. As an alternative explanation, two types of supply-side factors are tested: crowding-out effects and educational gaps in the workforce. The former seems non significant, whilst the effects of the latter disappear after controlling for the levels of institutional protection in standard employment during the 1980s. Multivariate analysis shows that only this latter institutional variable, together with the degree of coordinated centralisation of the collective bargaining system, seem to have a significant impact on the distribution of temporary employment in the countries examined. On the basis of this observation, an explanation of the very high levels of temporary employment observed in Spain is proposed. This explanation is consistent with both country-specific and comparative evidence.

Variations publicitaires sur le genre : une analyse linguistique des représentations publicitaires du féminin et du masculin

Résumé:¦Sur le plan économique, le système de genre est une pierre angulaire du discours publicitaire. Il intervient dans la segmentation des marchés, la sélection des médias et des supports, l'apparence extérieure des produits, le ton des campagnes, le choix des arguments de vente et, bien sûr, les scripts des annonces. En contrepartie, sur le plan symbolique, le discours publicitaire est un dépositaire privilégié des imaginaires de genre qui circulent dans son contexte de diffusion. En cette qualité, confronté à un marché toujours plus concurrentiel, à l'instabilité croissante des consommateurs ainsi qu'à une critique médiatique, académique et publique à l'affût des stéréotypes, le discours publicitaire est amené à proposer des représentations des hommes et des femmes de plus en plus diversifiées. Le présent ouvrage, qui relève de l'analyse linguistique des discours, rentre dans la complexité de ces variations publicitaires sur le féminin et le masculin et déchiffre les imaginaires de genre dont elles relèvent. Il soulève par ailleurs la question de la dimension politique des recherches académiques.