Snapshot gradient-recalled echo-planar images of rat brains at long echo time at 9.4 T.

With improved B 0 homogeneity along with satisfactory gradient performance at high magnetic fields, snapshot gradient-recalled echo-planar imaging (GRE-EPI) would perform at long echo times (TEs) on the order of T2*, which intrinsically allows obtaining strongly T2*-weighted images with embedded substantial anatomical details in ultrashort time. The aim of this study was to investigate the feasibility and quality of long TE snapshot GRE-EPI images of rat brain at 9.4 T. When compensating for B 0 inhomogeneities, especially second-order shim terms, a 200 x 200 microm2 in-plane resolution image was reproducibly obtained at long TE (>25 ms). The resulting coronal images at 30 ms had diminished geometric distortions and, thus, embedded substantial anatomical details. Concurrently with the very consistent stability, such GRE-EPI images should permit to resolve functional data not only with high specificity but also with substantial anatomical details, therefore allowing coregistration of the acquired functional data on the same image data set.

Dense deformation field estimation for atlas-based segmentation of pathological MR brain images.

Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.

Noninvasive characterization of the fission yeast cell cycle by monitoring dry mass with digital holographic microscopy.

Digital holography microscopy (DHM) is an optical technique which provides phase images yielding quantitative information about cell structure and cellular dynamics. Furthermore, the quantitative phase images allow the derivation of other parameters, including dry mass production, density, and spatial distribution. We have applied DHM to study the dry mass production rate and the dry mass surface density in wild-type and mutant fission yeast cells. Our study demonstrates the applicability of DHM as a tool for label-free quantitative analysis of the cell cycle and opens the possibility for its use in high-throughput screening.

Pseudomonas fluorescens CHA0 produces enantio-pyochelin, the optical antipode of the Pseudomonas aeruginosa siderophore pyochelin.

The siderophore pyochelin is made by a thiotemplate mechanism from salicylate and two molecules of cysteine. In Pseudomonas aeruginosa, the first cysteine residue is converted to its D-isoform during thiazoline ring formation whereas the second cysteine remains in its L-configuration, thus determining the stereochemistry of the two interconvertible pyochelin diastereoisomers as 4'R, 2''R, 4''R (pyochelin I) and 4'R, 2''S, 4''R (pyochelin II). Pseudomonas fluorescens CHA0 was found to make a different stereoisomeric mixture, which promoted growth under iron limitation in strain CHA0 and induced the expression of its biosynthetic genes, but was not recognized as a siderophore and signaling molecule by P. aeruginosa. Reciprocally, pyochelin promoted growth and induced pyochelin gene expression in P. aeruginosa, but was not functional in P. fluorescens. The structure of the CHA0 siderophore was determined by mass spectrometry, thin-layer chromatography, NMR, polarimetry, and chiral HPLC as enantio-pyochelin, the optical antipode of the P. aeruginosa siderophore pyochelin. Enantio-pyochelin was chemically synthesized and confirmed to be active in CHA0. Its potential biosynthetic pathway in CHA0 is discussed.

An Efficient Segmentation Method for Ultrasound Images based on a Semi-supervised Approach and Patch-based Features

Segmenting ultrasound images is a challenging problemwhere standard unsupervised segmentation methods such asthe well-known Chan-Vese method fail. We propose in thispaper an efficient segmentation method for this class ofimages. Our proposed algorithm is based on asemi-supervised approach (user labels) and the use ofimage patches as data features. We also consider thePearson distance between patches, which has been shown tobe robust w.r.t speckle noise present in ultrasoundimages. Our results on phantom and clinical data show avery high similarity agreement with the ground truthprovided by a medical expert.

Simultaneous Optical Recording in Multiple Cells by Digital Holographic Microscopy of Chloride Current Associated to Activation of the Ligand-Gated Chloride Channel GABA(A) Receptor.

Chloride channels represent a group of targets for major clinical indications. However, molecular screening for chloride channel modulators has proven to be difficult and time-consuming as approaches essentially rely on the use of fluorescent dyes or invasive patch-clamp techniques which do not lend themselves to the screening of large sets of compounds. To address this problem, we have developed a non-invasive optical method, based on digital holographic microcopy (DHM), allowing monitoring of ion channel activity without using any electrode or fluorescent dye. To illustrate this approach, GABA(A) mediated chloride currents have been monitored with DHM. Practically, we show that DHM can non-invasively provide the quantitative determination of transmembrane chloride fluxes mediated by the activation of chloride channels associated with GABA(A) receptors. Indeed through an original algorithm, chloride currents elicited by application of appropriate agonists of the GABA(A) receptor can be derived from the quantitative phase signal recorded with DHM. Finally, chloride currents can be determined and pharmacologically characterized non-invasively simultaneously on a large cellular sampling by DHM.

Quality of assessement of CMR images in the setting of the European cardiovascular magnetic resonance registry : description and validation of standardized criteria

l'imagerie par résonance magnétique (IRMC) est une technologie utilisée depuis les aimées quatre¬-vingts dans le monde de la cardiologie. Cette technique d'imagerie non-invasive permet d'acquérir Ses images du coeur en trois dimensions, dans n'importe quel, plan, sans application de radiation, et en haute résolution. Actuellement, cette technique est devenue un référence dans l'évaluation et 'l'investigation de différentes pathologies cardiaques. La morphologie cardiaque, la fonction des ventricules ainsi que leur contraction, la perfusion tissulaire ainsi que la viabilité tissulaire peuvent être caractérisés en utilisant différentes séquences d'imagerie. Cependant, cette technologie repose sur des principes physiques complexes et la mise en pratique de cette technique se heurte à la difficulté d'évaluer un organe en mouvement permanent. L'IRM cardiaque est donc sujette à différents artefacts qui perturbent l'interprétation des examens et peuvent diminuer la précision diagnostique de cette technique. A notre connaissance, la plupart des images d'IRMC sont analysées et interprétées sans évaluation rigoureuse de la qualité intrinsèque de l'examen. Jusqu'à présent, et à notre connaissance, aucun critère d'évaluation de la qualité des examens d'IRMC n'a été clairement déterminé. L'équipe d'IRMC du CHUV, dirigée par le Prof J. Schwitter, a recensé une liste de 35 critères qualitatifs et 12 critères quantitatifs évaluant la qualité d'un examen d'IRMC et les a introduit dans une grille d'évaluation. L'objet de cette étude est de décrire et de valider la reproductibilité des critères figurant dans cette grille d'évaluation, par l'interprétation simultanée d'examens IRMC par différents observateurs (cardiologues spécialisés en IRM, étudiant en médecine, infirmière spécialisée). Notre étude a permis de démontrer que les critères définis pour l'évaluation des examens d'IRMC sont robustes, et permettent une bonne reproductibilité intra- et inter-observateurs. Cette étude valide ainsi l'utilisation de ces critères de qualité dans le cadre de l'imagerie par résonance magnétique cardiaque. D'autres études sont encore nécessaires afin de déterminer l'impact de la qualité de l'image sur la précision diagnostique de cette technique. Les critères standardisés que nous avons validés seront utilisés pour évaluer la qualité des images dans le cadre d'une étude à échelle européenne relative à l'IRMC : "l'EuroCMR registry". Parmi les autres utilités visées par ces critères de qualité, citons notamment la possibilité d'avoir une référence d'évaluation de la qualité d'examen pour toutes les futures études cliniques utilisant la technologie d'IRMC, de permettre aux centres d'IRMC de quantifier leur niveau de qualité, voire de créer un certificat de standard de qualité pour ces centres, d'évaluer la reproductibilité de l'évaluation des images par différents observateurs d'un même centre, ou encore d'évaluer précisément la qualité des séquences développées à l'avenir dans le monde de l'IRMC.

Brain Surface Segmentation of Magnetic Resonance Images of the Fetus

In this work we present a method for the image analysisof Magnetic Resonance Imaging (MRI) of fetuses. Our goalis to segment the brain surface from multiple volumes(axial, coronal and sagittal acquisitions) of a fetus. Tothis end we propose a two-step approach: first, a FiniteGaussian Mixture Model (FGMM) will segment the image into3 classes: brain, non-brain and mixture voxels. Second, aMarkov Random Field scheme will be applied tore-distribute mixture voxels into either brain ornon-brain tissue. Our main contributions are an adaptedenergy computation and an extended neighborhood frommultiple volumes in the MRF step. Preliminary results onfour fetuses of different gestational ages will be shown.

A rapid and effective vignetting correction for quantitative microscopy

Images acquired using optical microscopes are inherently subject to vignetting effects due to imperfect illumination and image acquisition. However, such vignetting effects hamper accurate extraction of quantitative information from biological images, leading to less effective image segmentation and increased noise in the measurements. Here, we describe a rapid and effective method for vignetting correction, which generates an estimate for a correction function from the background fluorescence without the need to acquire additional calibration images. We validate the usefulness of this algorithm using artificially distorted images as a gold standard for assessing the accuracy of the applied correction and then demonstrate that this correction method enables the reliable detection of biologically relevant variation in cell populations. A simple user interface called FlattifY was developed and integrated into the image analysis platform YeastQuant to facilitate easy application of vignetting correction to a wide range of images.