219 resultados para Image principale de profil


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Evaluation of segmentation methods is a crucial aspect in image processing, especially in the medical imaging field, where small differences between segmented regions in the anatomy can be of paramount importance. Usually, segmentation evaluation is based on a measure that depends on the number of segmented voxels inside and outside of some reference regions that are called gold standards. Although some other measures have been also used, in this work we propose a set of new similarity measures, based on different features, such as the location and intensity values of the misclassified voxels, and the connectivity and the boundaries of the segmented data. Using the multidimensional information provided by these measures, we propose a new evaluation method whose results are visualized applying a Principal Component Analysis of the data, obtaining a simplified graphical method to compare different segmentation results. We have carried out an intensive study using several classic segmentation methods applied to a set of MRI simulated data of the brain with several noise and RF inhomogeneity levels, and also to real data, showing that the new measures proposed here and the results that we have obtained from the multidimensional evaluation, improve the robustness of the evaluation and provides better understanding about the difference between segmentation methods.

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Introduction et objectif: Lors d'essais cliniques, le pharmacien est responsable de la préparation et de la dispensation des médicaments à évaluer. Un article récent a toutefois montré que les aspects pharmaceutiques liés au contrôle de la dose administrée in fine étaient souvent mal contrôlés. Il peut exister une différence entre la dose nominale fournie par le certificat d'analyse du fabricant et la dose réellement administrée au sujet, biais qui se reporte en cascade sur l'estimation des paramètres pharmaco¬cinétiques (PK), comme la clairance ou le volume de distribution. Ce travail visait à évaluer les biais entachant la quantité de médicament réellement injectée (iv/sc) aux volontaires d'un essai clinique étudiant la PK et la relation dose-réponse d'un nouveau produit biotechnologique. Méthode: La dose de médicament administrée lors de l'essai clinique (D) a été calculée de la manière suivante: D = C ? V - pertes. La concentration du produit (C; titre nominal du fabricant) a été vérifiée par immuno-essai. Le volume de médicament injecté (V) a été déterminé pour chaque injection par pesée (n=72), en utilisant la masse de la seringue avant et après injection et la densité du produit. Enfin, une analyse in vitro a permis d'évaluer les pertes liées à l'adsorption du produit dans les lignes de perfusion et de choisir le dispositif adéquat in vivo. Résultats: La concentration du médicament s'est révélée proche du titre nominal (96 ± 7%), et a été utilisée comme référence. Le volume injecté était quant à lui entaché d'un biais systématique par rapport à la valeur théorique correspondant à 0.03 mL pour la dose minimale (i.e. 75% du volume à injecter à cette dose). Une analyse complémentaire a montré que cela s'expliquait par une réaspiration partielle de la solution médica-menteuse avant le retrait de la seringue après injection sc, due à l'élasticité du piston. En iv, le biais était par contre provoqué par une réaspiration du soluté de perfusion co-administré. Enfin, la mesure des quantités de médicament récupérées après injection dans le dispositif de perfusion a démontré des pertes minimales par adsorption. Discussion-conclusion: Cette étude confirme l'existence de biais inversement corrélés au volume et à la concentration du médicament administré, pouvant provoquer des erreurs importantes sur les paramètres PK. Ce problème est négligé ou insuffisamment considéré dans les protocoles de Phase I et nécessiterait une planification rigoureuse. Les procédures opératoires devraient attirer l'attention sur ce point crucial.

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Abstract :This article examines the interplay of text and image in The Fairy Tales of Charles Perrault (1977), translated by Angela Carter and illustrated by Martin Ware, as a form of intersemiotic dialogue that sheds new light on Carter's work. It argues that Ware's highly original artwork based on the translation not only calls into question the association of fairy tales with children's literature (which still characterizes Carter's translation), but also captures an essential if heretofore neglected aspect of Carter's creative process, namely the dynamics between translating, illustrating and rewriting classic tales. Several elements from Ware's illustrations are indeed taken up and elaborated on in The Bloody Chamber and Other Stories (1979), the collection of "stories about fairy stories" that made Carter famous. These include visual details and strategies that she transposed to the realm of writing, giving rise to reflections on the relation between visuality and textuality.RésuméCet article considère l'interaction du texte et de l'image dans les contes de Perrault traduits par Angela Carter et illustrés par Martin Ware (The Fairy Tales of Charles Perrault, 1977) comme une forme de dialogue intersémiotique particulièrement productif. Il démontre que les illustrations originales de Ware ne mettent pas seulement en question l'assimilation des contes à la littérature de jeunesse (qui est encore la perspective adoptée par la traductrice dans ce livre), mais permettent aussi de saisir un aspect essentiel bien que jusque là ignoré du procession de création dans l'oeuvre de Carter, à savoir la dynamique qui lie la traduction, l'illustration et la réécriture des contes classiques. Plusieurs éléments des illustrations de Ware sont ainsi repris et élaborés dans The Bloody Chamber and Other Stories (1979), la collection de "stories about fairy stories" qui rendit Carter célèbre. La transposition de détails et de stratégies visuelles dans l'écriture donnent ainsi l'occasion de réflexions sur les rapports entre la visualité et la textualité.

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In medical imaging, merging automated segmentations obtained from multiple atlases has become a standard practice for improving the accuracy. In this letter, we propose two new fusion methods: "Global Weighted Shape-Based Averaging" (GWSBA) and "Local Weighted Shape-Based Averaging" (LWSBA). These methods extend the well known Shape-Based Averaging (SBA) by additionally incorporating the similarity information between the reference (i.e., atlas) images and the target image to be segmented. We also propose a new spatially-varying similarity-weighted neighborhood prior model, and an edge-preserving smoothness term that can be used with many of the existing fusion methods. We first present our new Markov Random Field (MRF) based fusion framework that models the above mentioned information. The proposed methods are evaluated in the context of segmentation of lymph nodes in the head and neck 3D CT images, and they resulted in more accurate segmentations compared to the existing SBA.

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The repeated presentation of simple objects as well as biologically salient objects can cause the adaptation of behavioral and neural responses during the visual categorization of these objects. Mechanisms of response adaptation during repeated food viewing are of particular interest for better understanding food intake beyond energetic needs. Here, we measured visual evoked potentials (VEPs) and conducted neural source estimations to initial and repeated presentations of high-energy and low-energy foods as well as non-food images. The results of our study show that the behavioral and neural responses to food and food-related objects are not uniformly affected by repetition. While the repetition of images displaying low-energy foods and non-food modulated VEPs as well as their underlying neural sources and increased behavioral categorization accuracy, the responses to high-energy images remained largely invariant between initial and repeated encounters. Brain mechanisms when viewing images of high-energy foods thus appear less susceptible to repetition effects than responses to low-energy and non-food images. This finding is likely related to the superior reward value of high-energy foods and might be one reason why in particular high-energetic foods are indulged although potentially leading to detrimental health consequences.

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We present a novel filtering method for multispectral satellite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments carried out on multiclass one-against-all classification and target detection show the capabilities of the learned spatial filters.

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Iterative image reconstruction algorithms provide significant improvements over traditional filtered back projection in computed tomography (CT). Clinically available through recent advances in modern CT technology, iterative reconstruction enhances image quality through cyclical image calculation, suppressing image noise and artifacts, particularly blooming artifacts. The advantages of iterative reconstruction are apparent in traditionally challenging cases-for example, in obese patients, those with significant artery calcification, or those with coronary artery stents. In addition, as clinical use of CT has grown, so have concerns over ionizing radiation associated with CT examinations. Through noise reduction, iterative reconstruction has been shown to permit radiation dose reduction while preserving diagnostic image quality. This approach is becoming increasingly attractive as the routine use of CT for pediatric and repeated follow-up evaluation grows ever more common. Cardiovascular CT in particular, with its focus on detailed structural and functional analyses, stands to benefit greatly from the promising iterative solutions that are readily available.

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Measurement of arterial input function is a restrictive aspect for quantitative (18)F-FDG PET studies in rodents because of their small total blood volume and the related difficulties in withdrawing blood.

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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).

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In many European countries, image quality for digital x-ray systems used in screening mammography is currently specified using a threshold-detail detectability method. This is a two-part study that proposes an alternative method based on calculated detectability for a model observer: the first part of the work presents a characterization of the systems. Eleven digital mammography systems were included in the study; four computed radiography (CR) systems, and a group of seven digital radiography (DR) detectors, composed of three amorphous selenium-based detectors, three caesium iodide scintillator systems and a silicon wafer-based photon counting system. The technical parameters assessed included the system response curve, detector uniformity error, pre-sampling modulation transfer function (MTF), normalized noise power spectrum (NNPS) and detective quantum efficiency (DQE). Approximate quantum noise limited exposure range was examined using a separation of noise sources based upon standard deviation. Noise separation showed that electronic noise was the dominant noise at low detector air kerma for three systems; the remaining systems showed quantum noise limited behaviour between 12.5 and 380 µGy. Greater variation in detector MTF was found for the DR group compared to the CR systems; MTF at 5 mm(-1) varied from 0.08 to 0.23 for the CR detectors against a range of 0.16-0.64 for the DR units. The needle CR detector had a higher MTF, lower NNPS and higher DQE at 5 mm(-1) than the powder CR phosphors. DQE at 5 mm(-1) ranged from 0.02 to 0.20 for the CR systems, while DQE at 5 mm(-1) for the DR group ranged from 0.04 to 0.41, indicating higher DQE for the DR detectors and needle CR system than for the powder CR phosphor systems. The technical evaluation section of the study showed that the digital mammography systems were well set up and exhibiting typical performance for the detector technology employed in the respective systems.

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White-light cystoscopy and cytology are the standard tools to diagnose bladder cancer. White-light cystoscopy is excellent to detect macroscopic exophytic tumors, but its sensitivity is poor for flat tumors such as carcinoma in situ. Use of fluorescence cystoscopy during transurethral bladder resection improve tumor detection, particulary for carcinoma in situ. Fluorescence cystoscopy reduce residual tumor rate, especially for voluminous and multifocal tumors with consecutive lower recurrence. Fluorescence is now recommended to diagnose and treat bladder cancer.

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BACKGROUND AND STUDY AIMS: The current gold standard in Barrett's esophagus monitoring consists of four-quadrant biopsies every 1-2 cm in accordance with the Seattle protocol. Adding brush cytology processed by digital image cytometry (DICM) may further increase the detection of patients with Barrett's esophagus who are at risk of neoplasia. The aim of the present study was to assess the additional diagnostic value and accuracy of DICM when added to the standard histological analysis in a cross-sectional multicenter study of patients with Barrett's esophagus in Switzerland. METHODS: One hundred sixty-four patients with Barrett's esophagus underwent 239 endoscopies with biopsy and brush cytology. DICM was carried out on 239 cytology specimens. Measures of the test accuracy of DICM (relative risk, sensitivity, specificity, likelihood ratios) were obtained by dichotomizing the histopathology results (high-grade dysplasia or adenocarcinoma vs. all others) and DICM results (aneuploidy/intermediate pattern vs. diploidy). RESULTS: DICM revealed diploidy in 83% of 239 endoscopies, an intermediate pattern in 8.8%, and aneuploidy in 8.4%. An intermediate DICM result carried a relative risk (RR) of 12 and aneuploidy a RR of 27 for high-grade dysplasia/adenocarcinoma. Adding DICM to the standard biopsy protocol, a pathological cytometry result (aneuploid or intermediate) was found in 25 of 239 endoscopies (11%; 18 patients) with low-risk histology (no high-grade dysplasia or adenocarcinoma). During follow-up of 14 of these 18 patients, histological deterioration was seen in 3 (21%). CONCLUSION: DICM from brush cytology may add important information to a standard biopsy protocol by identifying a subgroup of BE-patients with high-risk cellular abnormalities.