Cross validation of experts versus registration methods for target localization in deep brain stimulation.

In the last five years, Deep Brain Stimulation (DBS) has become the most popular and effective surgical technique for the treatent of Parkinson's disease (PD). The Subthalamic Nucleus (STN) is the usual target involved when applying DBS. Unfortunately, the STN is in general not visible in common medical imaging modalities. Therefore, atlas-based segmentation is commonly considered to locate it in the images. In this paper, we propose a scheme that allows both, to perform a comparison between different registration algorithms and to evaluate their ability to locate the STN automatically. Using this scheme we can evaluate the expert variability against the error of the algorithms and we demonstrate that automatic STN location is possible and as accurate as the methods currently used.

Towards a diffusion image processing validation and accuracy prediction framework

Validation is the main bottleneck preventing theadoption of many medical image processing algorithms inthe clinical practice. In the classical approach,a-posteriori analysis is performed based on someobjective metrics. In this work, a different approachbased on Petri Nets (PN) is proposed. The basic ideaconsists in predicting the accuracy that will result froma given processing based on the characterization of thesources of inaccuracy of the system. Here we propose aproof of concept in the scenario of a diffusion imaginganalysis pipeline. A PN is built after the detection ofthe possible sources of inaccuracy. By integrating thefirst qualitative insights based on the PN withquantitative measures, it is possible to optimize the PNitself, to predict the inaccuracy of the system in adifferent setting. Results show that the proposed modelprovides a good prediction performance and suggests theoptimal processing approach.

Multi-source composite kernels for urban image classification

This letter presents advanced classification methods for very high resolution images. Efficient multisource information, both spectral and spatial, is exploited through the use of composite kernels in support vector machines. Weighted summations of kernels accounting for separate sources of spectral and spatial information are analyzed and compared to classical approaches such as pure spectral classification or stacked approaches using all the features in a single vector. Model selection problems are addressed, as well as the importance of the different kernels in the weighted summation.

Image quality assessment in digital mammography: part II. NPWE as a validated alternative for contrast detail analysis.

Assessment of image quality for digital x-ray mammography systems used in European screening programs relies mainly on contrast-detail CDMAM phantom scoring and requires the acquisition and analysis of many images in order to reduce variability in threshold detectability. Part II of this study proposes an alternative method based on the detectability index (d') calculated for a non-prewhitened model observer with an eye filter (NPWE). The detectability index was calculated from the normalized noise power spectrum and image contrast, both measured from an image of a 5 cm poly(methyl methacrylate) phantom containing a 0.2 mm thick aluminium square, and the pre-sampling modulation transfer function. This was performed as a function of air kerma at the detector for 11 different digital mammography systems. These calculated d' values were compared against threshold gold thickness (T) results measured with the CDMAM test object and against derived theoretical relationships. A simple relationship was found between T and d', as a function of detector air kerma; a linear relationship was found between d' and contrast-to-noise ratio. The values of threshold thickness used to specify acceptable performance in the European Guidelines for 0.10 and 0.25 mm diameter discs were equivalent to threshold calculated detectability indices of 1.05 and 6.30, respectively. The NPWE method is a validated alternative to CDMAM scoring for use in the image quality specification, quality control and optimization of digital x-ray systems for screening mammography.

Free-breathing whole-heart coronary MRA with 3D radial SSFP and self-navigated image reconstruction.

Respiratory motion is a major source of artifacts in cardiac magnetic resonance imaging (MRI). Free-breathing techniques with pencil-beam navigators efficiently suppress respiratory motion and minimize the need for patient cooperation. However, the correlation between the measured navigator position and the actual position of the heart may be adversely affected by hysteretic effects, navigator position, and temporal delays between the navigators and the image acquisition. In addition, irregular breathing patterns during navigator-gated scanning may result in low scan efficiency and prolonged scan time. The purpose of this study was to develop and implement a self-navigated, free-breathing, whole-heart 3D coronary MRI technique that would overcome these shortcomings and improve the ease-of-use of coronary MRI. A signal synchronous with respiration was extracted directly from the echoes acquired for imaging, and the motion information was used for retrospective, rigid-body, through-plane motion correction. The images obtained from the self-navigated reconstruction were compared with the results from conventional, prospective, pencil-beam navigator tracking. Image quality was improved in phantom studies using self-navigation, while equivalent results were obtained with both techniques in preliminary in vivo studies.

Le Linceul: une exploration par la bande dessinée des potentialités narratives de la (re)production de l'image christique

L'article aborde la façon dont la série BD Le Linceul (2003-2006) s'approprie, dans le cadre de la fiction et du récit d'action grand public, le contexte de la réception de l'image acheiropoïète du Saint Suaire, intégrant la référence à des enjeux théologiques et scientifiques au sein d'une histoire à suspense située à différentes époques et dont les nombreux rebondissements s'articulent autour d'une croyance progressive dans le statut sacré de la vera icon. L'examen détaillé de certains choix narratifs et graphiques de l'auteur Laurent Bidot permet de dégager les modalités d'une exploitation contemporaine et (a priori) laïcisée de la figure de Jésus qui, à l'ère des technologies numériques, conserve sa part de mystère. Dans une perspective narratologique, l'interprétation procède principalement de constats liés à l'organisation énonciative de cette production bédéique.

Brain dysfunctions, psychopathologies, and body image distortions

The major features in eating disorders are a preoccupation with food and its consumption and body dissatisfaction. Diagnostic manuals provide clusters of criteria according to which affected individuals can be categorized into one or other group of eating disorder. Yet, when considering the high proportion of comorbidities and ignoring the content of the symptoms (food, body), the major features seem to yield obsessional-compulsive, addictive, and impulsive qualities. In the present article, we review studies from the neuroscientific literature (mainly lesion studies) on eating disorder, obsessive-compulsive disorder, impulse control disorder, and addiction to investigate the possibility of a wider phenotype that can be related to a common brain network. The literature localizes this network to the right frontal lobe and its connectivities. This network, when dysfunctional, might result in a behavior that favors the preoccupation with particular thoughts, behaviors, anxieties, and uncontrollable urges that are accompanied by little scope for ongoing behavioral adjustments (e.g., impulse control). We reason that this network may turn out to be equally involved in understudied mental conditions of dysfunctional body processing such as muscle dysmorphia, body dysmorphic disorder (including esthetic surgery), and xelomelia. We finally consider previous notions of a wider phenotype approach to current diagnostic practice (using DSM), such as the possibility of a model with a reduced number of diagnostic categories and primary and secondary factors, and to etiological models of mental health conditions.

On the convergence of EM-like algorithms for image segmentation using Markov random fields.

Inference of Markov random field images segmentation models is usually performed using iterative methods which adapt the well-known expectation-maximization (EM) algorithm for independent mixture models. However, some of these adaptations are ad hoc and may turn out numerically unstable. In this paper, we review three EM-like variants for Markov random field segmentation and compare their convergence properties both at the theoretical and practical levels. We specifically advocate a numerical scheme involving asynchronous voxel updating, for which general convergence results can be established. Our experiments on brain tissue classification in magnetic resonance images provide evidence that this algorithm may achieve significantly faster convergence than its competitors while yielding at least as good segmentation results.

Occupational and patient exposure as well as image quality for full spine examinations with the EOS imaging system.

PURPOSE: EOS (EOS imaging S.A, Paris, France) is an x-ray imaging system that uses slot-scanning technology in order to optimize the trade-off between image quality and dose. The goal of this study was to characterize the EOS system in terms of occupational exposure, organ doses to patients as well as image quality for full spine examinations. METHODS: Occupational exposure was determined by measuring the ambient dose equivalents in the radiological room during a standard full spine examination. The patient dosimetry was performed using anthropomorphic phantoms representing an adolescent and a five-year-old child. The organ doses were measured with thermoluminescent detectors and then used to calculate effective doses. Patient exposure with EOS was then compared to dose levels reported for conventional radiological systems. Image quality was assessed in terms of spatial resolution and different noise contributions to evaluate the detector's performances of the system. The spatial-frequency signal transfer efficiency of the imaging system was quantified by the detective quantum efficiency (DQE). RESULTS: The use of a protective apron when the medical staff or parents have to stand near to the cubicle in the radiological room is recommended. The estimated effective dose to patients undergoing a full spine examination with the EOS system was 290μSv for an adult and 200 μSv for a child. MTF and NPS are nonisotropic, with higher values in the scanning direction; they are in addition energy-dependent, but scanning speed independent. The system was shown to be quantum-limited, with a maximum DQE of 13%. The relevance of the DQE for slot-scanning system has been addressed. CONCLUSIONS: As a summary, the estimated effective dose was 290μSv for an adult; the image quality remains comparable to conventional systems.

Automatic Decision-Oriented Mapping of Pollution Data

The paper deals with the development and application of the methodology for automatic mapping of pollution/contamination data. General Regression Neural Network (GRNN) is considered in detail and is proposed as an efficient tool to solve this problem. The automatic tuning of isotropic and an anisotropic GRNN model using cross-validation procedure is presented. Results are compared with k-nearest-neighbours interpolation algorithm using independent validation data set. Quality of mapping is controlled by the analysis of raw data and the residuals using variography. Maps of probabilities of exceeding a given decision level and ?thick? isoline visualization of the uncertainties are presented as examples of decision-oriented mapping. Real case study is based on mapping of radioactively contaminated territories.

GENCODE: producing a reference annotation for ENCODE.

BACKGROUND: The GENCODE consortium was formed to identify and map all protein-coding genes within the ENCODE regions. This was achieved by a combination of initial manual annotation by the HAVANA team, experimental validation by the GENCODE consortium and a refinement of the annotation based on these experimental results. RESULTS: The GENCODE gene features are divided into eight different categories of which only the first two (known and novel coding sequence) are confidently predicted to be protein-coding genes. 5' rapid amplification of cDNA ends (RACE) and RT-PCR were used to experimentally verify the initial annotation. Of the 420 coding loci tested, 229 RACE products have been sequenced. They supported 5' extensions of 30 loci and new splice variants in 50 loci. In addition, 46 loci without evidence for a coding sequence were validated, consisting of 31 novel and 15 putative transcripts. We assessed the comprehensiveness of the GENCODE annotation by attempting to validate all the predicted exon boundaries outside the GENCODE annotation. Out of 1,215 tested in a subset of the ENCODE regions, 14 novel exon pairs were validated, only two of them in intergenic regions. CONCLUSION: In total, 487 loci, of which 434 are coding, have been annotated as part of the GENCODE reference set available from the UCSC browser. Comparison of GENCODE annotation with RefSeq and ENSEMBL show only 40% of GENCODE exons are contained within the two sets, which is a reflection of the high number of alternative splice forms with unique exons annotated. Over 50% of coding loci have been experimentally verified by 5' RACE for EGASP and the GENCODE collaboration is continuing to refine its annotation of 1% human genome with the aid of experimental validation.

Body image perception and weight-related behaviour among adolescents of the Seychelles

Background: We examined one's own body image perception and its association with reported weight-related behavior among adolescents of a rapidly developing country in the African region. Methods: We conducted a school-based survey of 1432 students aged 11-17 years in the Seychelles. Weight and height were measured, and thinness, normal weight and overweight were assessed along standard criteria. A self-administered and anonymous questionnaire was administered. Perception of body image was assessed using both a closed-ended question (CEQ) and the Stunkard's pictorial silhouettes (SPS). Finally, a question assessed voluntary attempts to change weight. Results: Overall, 14.1% of the students were thin, 63.9% were normal-weight, and 22.0% were overweight or obese. There was fair agreement between actual weight status and self-perceived body image based on either CEQ or SPS. However, a substantial proportion of the overweight students did not consider themselves as overweight (SPS: 24%, CEQ: 34%) and, inversely, a substantial proportion of the normal-weight students considered themselves as too thin (SPS: 29%, CEQ: 15%). Among the overweight students, an adequate attempt to lose weight was reported more often by boys and girls who perceived themselves as overweight vs. not overweight (72-88% vs. 40-71%, p <0.05 for most comparisons). Among the normal-weight students, an inadequate attempt to gain weight was reported more often by boys and girls who perceived themselves as thin vs. not thin (27-68% vs. 11-19%, p <0.05). Girls had leaner own body ideals than boys. Conclusions: We found that substantial proportions of overweight students did not perceive themselves as overweight and/or did not want to lose weight and, inversely, that many normalweight students perceived themselves as too thin and/or wanted to gain weight: this points to forces that can drive the upwards overweight trends. Appropriate perception of one's weight was associated with adequate weight-control behavior, although not strongly, emphasizing that appropriate weight perception is only one of several factors driving adequate weight-related behavior. These findings emphasize the need to address appropriate perception of one's own weight and adequate weight-related behavior in adolescents for both individual and community weight-related interventions.