436 research outputs found

    Open source bioimage informatics for cell biology

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    Significant technical advances in imaging, molecular biology and genomics have fueled a revolution in cell biology, in that the molecular and structural processes of the cell are now visualized and measured routinely. Driving much of this recent development has been the advent of computational tools for the acquisition, visualization, analysis and dissemination of these datasets. These tools collectively make up a new subfield of computational biology called bioimage informatics, which is facilitated by open source approaches. We discuss why open source tools for image informatics in cell biology are needed, some of the key general attributes of what make an open source imaging application successful, and point to opportunities for further operability that should greatly accelerate future cell biology discovery

    Collaborative analysis of multi-gigapixel imaging data using Cytomine

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    Motivation: Collaborative analysis of massive imaging datasets is essential to enable scientific discoveries. Results: We developed Cytomine to foster active and distributed collaboration of multidisciplinary teams for large-scale image-based studies. It uses web development methodologies and machine learning in order to readily organize, explore, share and analyze (semantically and quantitatively) multi-gigapixel imaging data over the internet. We illustrate how it has been used in several biomedical applications

    BioIMAX : a Web2.0 approach to visual data mining in bioimage data

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    Loyek C. BioIMAX : a Web2.0 approach to visual data mining in bioimage data. Bielefeld: Universität Bielefeld; 2012

    A call for public archives for biological image data

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    Public data archives are the backbone of modern biological and biomedical research. While archives for biological molecules and structures are well-established, resources for imaging data do not yet cover the full range of spatial and temporal scales or application domains used by the scientific community. In the last few years, the technical barriers to building such resources have been solved and the first examples of scientific outputs from public image data resources, often through linkage to existing molecular resources, have been published. Using the successes of existing biomolecular resources as a guide, we present the rationale and principles for the construction of image data archives and databases that will be the foundation of the next revolution in biological and biomedical informatics and discovery.Comment: 13 pages, 1 figur

    ImageJ2: ImageJ for the next generation of scientific image data

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    ImageJ is an image analysis program extensively used in the biological sciences and beyond. Due to its ease of use, recordable macro language, and extensible plug-in architecture, ImageJ enjoys contributions from non-programmers, amateur programmers, and professional developers alike. Enabling such a diversity of contributors has resulted in a large community that spans the biological and physical sciences. However, a rapidly growing user base, diverging plugin suites, and technical limitations have revealed a clear need for a concerted software engineering effort to support emerging imaging paradigms, to ensure the software's ability to handle the requirements of modern science. Due to these new and emerging challenges in scientific imaging, ImageJ is at a critical development crossroads. We present ImageJ2, a total redesign of ImageJ offering a host of new functionality. It separates concerns, fully decoupling the data model from the user interface. It emphasizes integration with external applications to maximize interoperability. Its robust new plugin framework allows everything from image formats, to scripting languages, to visualization to be extended by the community. The redesigned data model supports arbitrarily large, N-dimensional datasets, which are increasingly common in modern image acquisition. Despite the scope of these changes, backwards compatibility is maintained such that this new functionality can be seamlessly integrated with the classic ImageJ interface, allowing users and developers to migrate to these new methods at their own pace. ImageJ2 provides a framework engineered for flexibility, intended to support these requirements as well as accommodate future needs

    Aragon workers’ health study – design and cohort description

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    BACKGROUND: Spain, a Mediterranean country with relatively low rates of coronary heart disease, has a high prevalence of traditional cardiovascular risk factors and is experiencing a severe epidemic of overweight/obesity. We designed the Aragon Workers’ Health Study (AWHS) to characterize the factors associated with metabolic abnormalities and subclinical atherosclerosis in a middle aged population in Spain free of clinical cardiovascular disease. The objective of this paper is to describe the study design, aims and baseline characteristics of participants in the AWHS. METHODS/DESIGN: Longitudinal cohort study based on the annual health exams of 5,400 workers of a car assembly plant in Figueruelas (Zaragoza, Spain). Study participants were recruited during a standardized clinical exam in 2009–2010 (participation rate 95.6%). Study participants will undergo annual clinical exams and laboratory assays, and baseline and triennial collection of biological materials for biobanking and cardiovascular imaging exams (carotid, femoral and abdominal ultrasonography, coronary calcium score, and ankle-arm blood pressure index). Participants will be followed-up for 10 years. RESULTS: The average (SD) age, body mass index, and waist circumference were 49.3 (8.7) years, 27.7 (3.6) kg/m(2) and 97.2 (9.9) cm, respectively, among males (N = 5,048), and 40.8 (11.6) years, 24.4 (3.8) kg/m(2), and 81.9 (9.9) cm, among females (N = 351). The prevalence of overweight, obesity, current smoking, hypertension, hypercholesterolemia, and diabetes were 55.0, 23.1, 37.1, 40.3, 75.0, and 7.4%, respectively, among males, and 23.7, 8.3, 45.0, 12.1, 59.5, and 0.6%, respectively, among females. In the initial 587 study participants who completed all imaging exams (94.5% male), the prevalence of carotid plaque, femoral plaque, coronary calcium score >1 to 100, and coronary calcium score >100 was 30.3, 56.9, 27.0, and 8.8%, respectively. 67.7% of study participants had at least one plaque in the carotid or femoral arteries. DISCUSSION: Baseline data from the AWHS show a high prevalence of cardiovascular risk factors and of sublinical atherosclerosis. Follow-up of this cohort will allow the assessment of subclinical atherosclerosis progression and the link of disease progression to traditional and emergent risk factors
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