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High-throughput image reconstruction and analysis /

Explore the latest developments in bioimaging, image analysis, and data mining with the first comprehensive book on innovative high-performance computing (HPC) techniques that are facilitating never-before research capabilities and applications. This unique resource demonstrates how HPC can solve th...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Ravishankar Rao, A., Cecchi, Guillermo A.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Norwood, MA : Artech House, ©2009.
Colección:Artech House bioinformatics & biomedical imaging series.
Temas:
Acceso en línea:Texto completo

MARC

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245 0 0 |a High-throughput image reconstruction and analysis /  |c A. Ravishankar Rao, Guillermo A. Cecchi, editors. 
260 |a Norwood, MA :  |b Artech House,  |c ©2009. 
300 |a 1 online resource (xii, 339 pages) :  |b illustrations 
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490 1 |a Bioinformatics & biomedical imaging 
504 |a Includes bibliographical references and index. 
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505 0 |a pt. 1. Emerging technologies to understand biological systems -- pt. 2. Understanding and utilizing parallel processing techniques -- pt. 3. Specific applications of parallel computing -- pt. 4. Post processing. 
520 3 |a Explore the latest developments in bioimaging, image analysis, and data mining with the first comprehensive book on innovative high-performance computing (HPC) techniques that are facilitating never-before research capabilities and applications. This unique resource demonstrates how HPC can solve the data bottleneck created by today's microscopy techniques. It provides state-of-the-art methods and algorithms for building complex models from large biological datasets and solving data analysis and interpretation problems. This innovative volume surveys the latest image acquisition advances in serial block face techniques in scanning electron microscopy, knife-edge scanning microscopy, and 4D imaging of multi-component biological systems. The book introduces parallel processing for biological applications. You learn advanced parallelization techniques for decomposing a problem domain and mapping it onto a parallel processing architecture using the message-passing interface (MPI) and OpenMP. Case studies show how these techniques have been successfully used in simulation tasks, data mining, and graphical visualization of biological datasets. You also find coverage of methods for developing scalable biological image databases and for facilitating greater interactive visualization of large image sets.  |c Publisher abstract. 
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650 0 |a Imaging systems in biology. 
650 0 |a Biology  |x Data processing. 
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650 0 |a Computational biology. 
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700 1 |a Ravishankar Rao, A. 
700 1 |a Cecchi, Guillermo A. 
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