From Translation to Rewriting : the Interplay of Text and Image in The Fairy Tales of Charles Perrault and The Bloody Chamber and Other Stories

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.

The Figure of Radha in Miniature Paintings: From the Pastoral to the Courtly, from Text to Visuality, from Polyphony to Normativity

This article analyses how Radha was depicted in miniature paintings between the 16th and 19th century in North India. Interrogating the link between text and image, contrasting poetry, style and historical settings with the visual representations of this central figure, my reflections focus on the changing nature of Radha. Through various examples from miniature paintings of different periods and schools, this article analyses the way the rich personality of Radha was transposed into images. In order to stress the changes brought to this female figure, I compare her to Krishna, the masculine figure who is always at her side. The main goal of the article is to show the normative power of images on the figure of Radha, with normativity being understood as the simplification, iconisation, aestheticisation and stereotypification of a figure with polysemous references.

trEST, trGEN and Hits: access to databases of predicted protein sequences.

High throughput genome (HTG) and expressed sequence tag (EST) sequences are currently the most abundant nucleotide sequence classes in the public database. The large volume, high degree of fragmentation and lack of gene structure annotations prevent efficient and effective searches of HTG and EST data for protein sequence homologies by standard search methods. Here, we briefly describe three newly developed resources that should make discovery of interesting genes in these sequence classes easier in the future, especially to biologists not having access to a powerful local bioinformatics environment. trEST and trGEN are regularly regenerated databases of hypothetical protein sequences predicted from EST and HTG sequences, respectively. Hits is a web-based data retrieval and analysis system providing access to precomputed matches between protein sequences (including sequences from trEST and trGEN) and patterns and profiles from Prosite and Pfam. The three resources can be accessed via the Hits home page (http://hits. isb-sib.ch).

How Low Can We Go in Contrast-Enhanced CT Imaging of the Chest?: A Dose-Finding Cadaver Study Using the Model-based Iterative Image Reconstruction Approach.

RATIONALE AND OBJECTIVES: Dose reduction may compromise patients because of a decrease of image quality. Therefore, the amount of dose savings in new dose-reduction techniques needs to be thoroughly assessed. To avoid repeated studies in one patient, chest computed tomography (CT) scans with different dose levels were performed in corpses comparing model-based iterative reconstruction (MBIR) as a tool to enhance image quality with current standard full-dose imaging. MATERIALS AND METHODS: Twenty-five human cadavers were scanned (CT HD750) after contrast medium injection at different, decreasing dose levels D0-D5 and respectively reconstructed with MBIR. The data at full-dose level, D0, have been additionally reconstructed with standard adaptive statistical iterative reconstruction (ASIR), which represented the full-dose baseline reference (FDBR). Two radiologists independently compared image quality (IQ) in 3-mm multiplanar reformations for soft-tissue evaluation of D0-D5 to FDBR (-2, diagnostically inferior; -1, inferior; 0, equal; +1, superior; and +2, diagnostically superior). For statistical analysis, the intraclass correlation coefficient (ICC) and the Wilcoxon test were used. RESULTS: Mean CT dose index values (mGy) were as follows: D0/FDBR = 10.1 ± 1.7, D1 = 6.2 ± 2.8, D2 = 5.7 ± 2.7, D3 = 3.5 ± 1.9, D4 = 1.8 ± 1.0, and D5 = 0.9 ± 0.5. Mean IQ ratings were as follows: D0 = +1.8 ± 0.2, D1 = +1.5 ± 0.3, D2 = +1.1 ± 0.3, D3 = +0.7 ± 0.5, D4 = +0.1 ± 0.5, and D5 = -1.2 ± 0.5. All values demonstrated a significant difference to baseline (P < .05), except mean IQ for D4 (P = .61). ICC was 0.91. CONCLUSIONS: Compared to ASIR, MBIR allowed for a significant dose reduction of 82% without impairment of IQ. This resulted in a calculated mean effective dose below 1 mSv.

Trabecular Bone Score: A Noninvasive Analytical Method Based Upon the DXA Image.

The trabecular bone score (TBS) is a gray-level textural metric that can be extracted from the two-dimensional lumbar spine dual-energy X-ray absorptiometry (DXA) image. TBS is related to bone microarchitecture and provides skeletal information that is not captured from the standard bone mineral density (BMD) measurement. Based on experimental variograms of the projected DXA image, TBS has the potential to discern differences between DXA scans that show similar BMD measurements. An elevated TBS value correlates with better skeletal microstructure; a low TBS value correlates with weaker skeletal microstructure. Lumbar spine TBS has been evaluated in cross-sectional and longitudinal studies. The following conclusions are based upon publications reviewed in this article: 1) TBS gives lower values in postmenopausal women and in men with previous fragility fractures than their nonfractured counterparts; 2) TBS is complementary to data available by lumbar spine DXA measurements; 3) TBS results are lower in women who have sustained a fragility fracture but in whom DXA does not indicate osteoporosis or even osteopenia; 4) TBS predicts fracture risk as well as lumbar spine BMD measurements in postmenopausal women; 5) efficacious therapies for osteoporosis differ in the extent to which they influence the TBS; 6) TBS is associated with fracture risk in individuals with conditions related to reduced bone mass or bone quality. Based on these data, lumbar spine TBS holds promise as an emerging technology that could well become a valuable clinical tool in the diagnosis of osteoporosis and in fracture risk assessment. © 2014 American Society for Bone and Mineral Research.

Weighted Shape-based Averaging with Neighborhood Prior Model for Multiple Atlas Fusion-based Medical Image Segmentation

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.

VIKI : a semiotic-based system for multilingual knowledge retrieval

Abstract Since its creation, the Internet has permeated our daily life. The web is omnipresent for communication, research and organization. This exploitation has resulted in the rapid development of the Internet. Nowadays, the Internet is the biggest container of resources. Information databases such as Wikipedia, Dmoz and the open data available on the net are a great informational potentiality for mankind. The easy and free web access is one of the major feature characterizing the Internet culture. Ten years earlier, the web was completely dominated by English. Today, the web community is no longer only English speaking but it is becoming a genuinely multilingual community. The availability of content is intertwined with the availability of logical organizations (ontologies) for which multilinguality plays a fundamental role. In this work we introduce a very high-level logical organization fully based on semiotic assumptions. We thus present the theoretical foundations as well as the ontology itself, named Linguistic Meta-Model. The most important feature of Linguistic Meta-Model is its ability to support the representation of different knowledge sources developed according to different underlying semiotic theories. This is possible because mast knowledge representation schemata, either formal or informal, can be put into the context of the so-called semiotic triangle. In order to show the main characteristics of Linguistic Meta-Model from a practical paint of view, we developed VIKI (Virtual Intelligence for Knowledge Induction). VIKI is a work-in-progress system aiming at exploiting the Linguistic Meta-Model structure for knowledge expansion. It is a modular system in which each module accomplishes a natural language processing task, from terminology extraction to knowledge retrieval. VIKI is a supporting system to Linguistic Meta-Model and its main task is to give some empirical evidence regarding the use of Linguistic Meta-Model without claiming to be thorough.

Trabecular bone score: a noninvasive analytical method based upon the DXA image.

The trabecular bone score (TBS) is a gray-level textural metric that can be extracted from the two-dimensional lumbar spine dual-energy X-ray absorptiometry (DXA) image. TBS is related to bone microarchitecture and provides skeletal information that is not captured from the standard bone mineral density (BMD) measurement. Based on experimental variograms of the projected DXA image, TBS has the potential to discern differences between DXA scans that show similar BMD measurements. An elevated TBS value correlates with better skeletal microstructure; a low TBS value correlates with weaker skeletal microstructure. Lumbar spine TBS has been evaluated in cross-sectional and longitudinal studies. The following conclusions are based upon publications reviewed in this article: 1) TBS gives lower values in postmenopausal women and in men with previous fragility fractures than their nonfractured counterparts; 2) TBS is complementary to data available by lumbar spine DXA measurements; 3) TBS results are lower in women who have sustained a fragility fracture but in whom DXA does not indicate osteoporosis or even osteopenia; 4) TBS predicts fracture risk as well as lumbar spine BMD measurements in postmenopausal women; 5) efficacious therapies for osteoporosis differ in the extent to which they influence the TBS; 6) TBS is associated with fracture risk in individuals with conditions related to reduced bone mass or bone quality. Based on these data, lumbar spine TBS holds promise as an emerging technology that could well become a valuable clinical tool in the diagnosis of osteoporosis and in fracture risk assessment.

Atlas-based segmentation of pathological MR brain images using a model of lesion growth.

We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.

Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches.

In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.

Influence of magnetic field strength and image registration strategy on voxel-based morphometry in a study of Alzheimer's disease.

Multi-centre data repositories like the Alzheimer's Disease Neuroimaging Initiative (ADNI) offer a unique research platform, but pose questions concerning comparability of results when using a range of imaging protocols and data processing algorithms. The variability is mainly due to the non-quantitative character of the widely used structural T1-weighted magnetic resonance (MR) images. Although the stability of the main effect of Alzheimer's disease (AD) on brain structure across platforms and field strength has been addressed in previous studies using multi-site MR images, there are only sparse empirically-based recommendations for processing and analysis of pooled multi-centre structural MR data acquired at different magnetic field strengths (MFS). Aiming to minimise potential systematic bias when using ADNI data we investigate the specific contributions of spatial registration strategies and the impact of MFS on voxel-based morphometry in AD. We perform a whole-brain analysis within the framework of Statistical Parametric Mapping, testing for main effects of various diffeomorphic spatial registration strategies, of MFS and their interaction with disease status. Beyond the confirmation of medial temporal lobe volume loss in AD, we detect a significant impact of spatial registration strategy on estimation of AD related atrophy. Additionally, we report a significant effect of MFS on the assessment of brain anatomy (i) in the cerebellum, (ii) the precentral gyrus and (iii) the thalamus bilaterally, showing no interaction with the disease status. We provide empirical evidence in support of pooling data in multi-centre VBM studies irrespective of disease status or MFS.

Model-based Segmentation and Image Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

For radiotherapy treatment planning of retinoblastoma inchildhood, Computed Tomography (CT) represents thestandard method for tumor volume delineation, despitesome inherent limitations. CT scan is very useful inproviding information on physical density for dosecalculation and morphological volumetric information butpresents a low sensitivity in assessing the tumorviability. On the other hand, 3D ultrasound (US) allows ahigh accurate definition of the tumor volume thanks toits high spatial resolution but it is not currentlyintegrated in the treatment planning but used only fordiagnosis and follow-up. Our ultimate goal is anautomatic segmentation of gross tumor volume (GTV) in the3D US, the segmentation of the organs at risk (OAR) inthe CT and the registration of both. In this paper, wepresent some preliminary results in this direction. Wepresent 3D active contour-based segmentation of the eyeball and the lens in CT images; the presented approachincorporates the prior knowledge of the anatomy by usinga 3D geometrical eye model. The automated segmentationresults are validated by comparing with manualsegmentations. Then, for the fusion of 3D CT and USimages, we present two approaches: (i) landmark-basedtransformation, and (ii) object-based transformation thatmakes use of eye ball contour information on CT and USimages.

Model-based iterative reconstruction in pediatric chest CT: assessment of image quality in a prospective study of children with cystic fibrosis.

BACKGROUND: The potential effects of ionizing radiation are of particular concern in children. The model-based iterative reconstruction VEO(TM) is a technique commercialized to improve image quality and reduce noise compared with the filtered back-projection (FBP) method. OBJECTIVE: To evaluate the potential of VEO(TM) on diagnostic image quality and dose reduction in pediatric chest CT examinations. MATERIALS AND METHODS: Twenty children (mean 11.4 years) with cystic fibrosis underwent either a standard CT or a moderately reduced-dose CT plus a minimum-dose CT performed at 100 kVp. Reduced-dose CT examinations consisted of two consecutive acquisitions: one moderately reduced-dose CT with increased noise index (NI = 70) and one minimum-dose CT at CTDIvol 0.14 mGy. Standard CTs were reconstructed using the FBP method while low-dose CTs were reconstructed using FBP and VEO. Two senior radiologists evaluated diagnostic image quality independently by scoring anatomical structures using a four-point scale (1 = excellent, 2 = clear, 3 = diminished, 4 = non-diagnostic). Standard deviation (SD) and signal-to-noise ratio (SNR) were also computed. RESULTS: At moderately reduced doses, VEO images had significantly lower SD (P < 0.001) and higher SNR (P < 0.05) in comparison to filtered back-projection images. Further improvements were obtained at minimum-dose CT. The best diagnostic image quality was obtained with VEO at minimum-dose CT for the small structures (subpleural vessels and lung fissures) (P < 0.001). The potential for dose reduction was dependent on the diagnostic task because of the modification of the image texture produced by this reconstruction. CONCLUSIONS: At minimum-dose CT, VEO enables important dose reduction depending on the clinical indication and makes visible certain small structures that were not perceptible with filtered back-projection.

Application of text-mining for updating protein post-translational modification annotation in UniProtKB.

BACKGROUND: The annotation of protein post-translational modifications (PTMs) is an important task of UniProtKB curators and, with continuing improvements in experimental methodology, an ever greater number of articles are being published on this topic. To help curators cope with this growing body of information we have developed a system which extracts information from the scientific literature for the most frequently annotated PTMs in UniProtKB. RESULTS: The procedure uses a pattern-matching and rule-based approach to extract sentences with information on the type and site of modification. A ranked list of protein candidates for the modification is also provided. For PTM extraction, precision varies from 57% to 94%, and recall from 75% to 95%, according to the type of modification. The procedure was used to track new publications on PTMs and to recover potential supporting evidence for phosphorylation sites annotated based on the results of large scale proteomics experiments. CONCLUSIONS: The information retrieval and extraction method we have developed in this study forms the basis of a simple tool for the manual curation of protein post-translational modifications in UniProtKB/Swiss-Prot. Our work demonstrates that even simple text-mining tools can be effectively adapted for database curation tasks, providing that a thorough understanding of the working process and requirements are first obtained. This system can be accessed at http://eagl.unige.ch/PTM/.