30 research outputs found

    Task-based Augmented Reeb Graphs with Dynamic ST-Trees

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    International audienceThis paper presents, to the best of our knowledge, the first parallel algorithm for the computation of the augmented Reeb graph of piecewise linear scalar data. Such augmented Reeb graphs have a wide range of applications , including contour seeding and feature based segmentation. Our approach targets shared-memory multi-core workstations. For this, it completely revisits the optimal, but sequential, Reeb graph algorithm, which is capable of handing data in arbitrary dimension and with optimal time complexity. We take advantage of Fibonacci heaps to exploit the ST-Tree data structure through independent local propagations, while maintaining the optimal, linearithmic time complexity of the sequential reference algorithm. These independent propagations can be expressed using OpenMP tasks, hence benefiting in parallel from the dynamic load balancing of the task runtime while enabling us to increase the parallelism degree thanks to a dual sweep. We present performance results on triangulated surfaces and tetrahedral meshes. We provide comparisons to related work and show that our new algorithm results in superior time performance in practice, both in sequential and in parallel. An open-source C++ implementation is provided for reproducibility

    An Open-Source Digital Archiving System for Medical and Scientific Research

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    In this paper, we present MIDAS, an open-source web-based digital archiving system that handles large collections of scientific data. We created a web-based digital archiving repository based on open standards. The MIDAS repository is specifically tuned for medical and scientific datasets and provides a flexible data management facility, a search engine, and an online image viewer. MIDAS allows researchers to store, manage and share scientific datasets, from the convenience of a web browser or through a generic programming interface, thereby facilitating the dissemination of valuable imaging datasets to research collaborators. The system is currently deployed at several research laboratories worldwide and has demonstrated its ability to streamline the full scientific processing workflow from data acquisition to analysis and reports

    An Open-Source Digital Archiving System for Medical and Scientific Research

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    In this paper, we present MIDAS, an open-source web-based digital archiving system that handles large collections of scientific data. We created a web-based digital archiving repository based on open standards. The MIDAS repository is specifically tuned for medical and scientific datasets and provides a flexible data management facility, a search engine, and an online image viewer. MIDAS allows researchers to store, manage and share scientific datasets, from the convenience of a web browser or through a generic programming interface, thereby facilitating the dissemination of valuable imaging datasets to research collaborators. The system is currently deployed at several research laboratories worldwide and has demonstrated its ability to streamline the full scientific processing workflow from data acquisition to analysis and reports

    From medical imaging to numerical simulations

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    International audienceIn the last 20 years there have been lots of progress in 3D medical imaging (such as Magnetic Resonance Imaging, MRI, and X-ray Computed Tomography, CT) and in particular in modalities to visualise vascular structures. The resulting images have been successfully used in various clinical applications, in particular for cerebrovascular pathologies (e.g., neurosurgery planning; stenoses, aneurysm or thrombosis quantification; arteriovenous malformation detection and follow-up, etc.). The complexity of the processing and analysis of these images (size, information vs noise, artifacts, etc) led to the development of imaging tools such as vessel filtering, segmentation and quantification. There is however, until now, no database of synthetic images and associated ground-truths (segmented data) available in cerebrovascular images contrary to morphological brain image analysis (e.g. brainweb).In the ANR Vivabrain project, we combine the skills of several communities: computer science, applied mathematics, biophysics, and medicine to remedy the aforementioned observation. In particular we focus on complex multi-disciplinary problems such as (i) the handling of inter-individual cerebrovascular variability, (ii) the generation of computational meshes, (iii) the simulation of blood flows in the complete cerebrovascular system 3D+time (3D+t) including calibration and validation and (iv) the accurate simulation of the physical processes involved in MRA acquisition sequences in order to finally obtain realistic virtual angiographic images

    Evaluation of atlas based mouse brain segmentation

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    Magentic Reasonance Imaging for mouse phenotype study is one of the important tools to understand human diseases. In this paper, we present a fully automatic pipeline for the process of morphometric mouse brain analysis. The method is based on atlas-based tissue and regional segmentation, which was originally developed for the human brain. To evaluate our method, we conduct a qualitative and quantitative validation study as well as compare of b-spline and fluid registration methods as components in the pipeline. The validation study includes visual inspection, shape and volumetric measurements and stability of the registration methods against various parameter settings in the processing pipeline. The result shows both fluid and b-spline registration methods work well in murine settings, but the fluid registration is more stable. Additionally, we evaluated our segmentation methods by comparing volume differences between Fmr1 FXS in FVB background vs C57BL/6J mouse strains

    ANGIOTK : An Open Platform to reconstruct vessels from MRI images and simulate blood flows to ultimately provide Virtual Angiographies

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    National audienceFrom medical images to numerical simulations ANGIOTK The platform is still a prototype, but reached a level of maturity that requires very little human intervention. The overall objective is to make available, to the medical community, tools for computer aided modeling for conducting experiments in silico, otherwise difficult or impossible to carry on patients. A specific aim is to create an ecosystem around the platform composed of academic, research centers and enterprises and to provide services such as training, specific developments, consulting or deployment. The platform is operated by Cemosis and Kitware. An Open Platform to reconstruct vessels from MRI images and simulate blood flows to ultimately provide Virtual Angiographie

    Registration and Analysis of Vascular Images

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    We have developed a method for rigidly aligning images of tubes. This paper presents an evaluation of the consistency of that method for three-dimensional images of human vasculature. Vascular images may contain alignment ambiguities, poorly corresponding vascular networks, and non-rigid deformations, yet the Monte Carlo experiments presented in this paper show that our method provides registrations with sub-voxel consistency in less than one minute. Our registration method builds on the principals of our ridges-and-widths tube modeling work; this registration method operates by aligning models of the tubes in a source image with subsequent target images. The registration method’s consistency results from incorporate multi-scale ridge and width measures into the model-image match metric. The method’s speed comes from the use of coarse-to-fine registration strategies that are directly enabled by our tube models and the model-image match metric. In this paper we also show that the method’s insensitivity to local, non-rigid deformations enables the visualization and quantification of the effects of such deformations

    Evaluation of atlas based mouse brain segmentation

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    Magentic Reasonance Imaging for mouse phenotype study is one of the important tools to understand human diseases. In this paper, we present a fully automatic pipeline for the process of morphometric mouse brain analysis. The method is based on atlas-based tissue and regional segmentation, which was originally developed for the human brain. To evaluate our method, we conduct a qualitative and quantitative validation study as well as compare of b-spline and fluid registration methods as components in the pipeline. The validation study includes visual inspection, shape and volumetric measurements and stability of the registration methods against various parameter settings in the processing pipeline. The result shows both fluid and b-spline registration methods work well in murine settings, but the fluid registration is more stable. Additionally, we evaluated our segmentation methods by comparing volume differences between Fmr1 FXS in FVB background vs C57BL/6J mouse strains

    Large Data Visualization with Open-Source Tools

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    Visualization and post-processing of large data have become increasingly challenging and require more and more tools to support the diversity of data to process. In this seminar, we will present a suite of open-source tools supported and developed by Kitware to perform large-scale data visualization and analysis. In particular, we will present ParaView, an open-source tool for parallel visualization of massive datasets, the Visualization Toolkit (VTK), an open-source toolkit for scientific visualization, and Tangelohub, a suite of tools for large data analytics. About the speaker Julien Jomier is directing Kitware's European subsidiary in Lyon, France, where he focuses on European business development. Julien works on a variety of projects in the areas of parallel and distributed computing, mobile computing, image processing, and visualization. He is one of the developers of the Insight Toolkit (ITK), the Visualization Toolkit (VTK), and ParaView. Julien is also leading the CDash project, an open-source continuous integration tool companion for CMake. </p

    Thomas Hardy, John Stuart Mill and Feminism

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    This study will investigate the relations to liberal feminism of Thomas Hardy’s novels Tess of the d’Urbervilles (1891) and Jude the Obscure (1895). I argue against those who believe Tess and Sue are victims, introducing them as proto-feminists by reading these two novels along with John Stuart Mill’s liberal feminist arguments. This study is consolidated by demonstrating how Hardy’s tragic novelistic form in these two works is connected to feminist content. The death of the female protagonists shows the difficulty of accommodating liberal feminist ideas within late Victorian society
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