High-Throughput Image Reconstruction and Analysis
Published in January 2009
Book
Hardback
380 pages
978-1-59693-295-1 (ISBN)
Description
Today's bioimaging technologies generate mountains of biological data that can simply overwhelm conventional analysis methods. This groundbreaking book helps researchers blast through the computational bottleneck with high-performance computing (HPC) techniques that are blazing the way to never-before bioimaging, image analysis, and data mining capabilities and revolutionizing the study of cellular and organ-level systems. This innovative volume surveys the latest advances in scanning electron microscopy, knife-edge scanning microscopy, and 4D imaging of multi-component biological systems. The book includes detailed case studies that show how key techniques have been successfully deployed in medical image analysis, drug discovery, tissue analysis, functional MRI data analysis, and other areas.
More details
Edition
Unabridged edition
Language
English
Place of publication
Norwood
United States
Target group
Professional and scholarly
Edition type
Unabridged edition
ISBN-13
978-1-59693-295-1 (9781596932951)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
A. Ravishankar Rao
High-Throughput Image Reconstruction and Analysis
E-Book
01/2008
1st Edition
Artech House
€129.99
Available for download
Persons
A. Ravishankar Rao is a research staff member with the Biometaphorical Computing Group at the IBM T.J. Watson Research Center, Yorktown Heights, New York. He is also an associate editor of the journals Pattern Recognition and Machine Vision and Applications. He was named a Master Inventor at IBM Research in 2004. Guillermo A. Cecchi is a research staff member with the Biometaphorical Computing Group at the IBM T.J. Watson Research Center, Yorktown Heights, New York. He also served as a postdoctoral fellow at Cornell University.
Content
Image Acquisition I: Serial Block Face Scanning Using High-Resolution Scanning Electron Microscopy.; Image Acquisition II: Knife-Edge Scanning Microscope.; Image Acquisition III: 4D Imaging of Multi-Component Biological Systems.; 4D Image Analysis I: Feature Extraction on Parallel Machines.; 4D Image Analysis II: Parallel Data Mining. gridImage Microscopy. High-Throughput Image-Based Screening. Laser Capture Microdissection. Applications of High-Performance Computing to Functional Magnetic Resonance Imaging (fMRI) Data. Databases for Bioimaging. Interactive Visualization of Large Image Datasets. Conclusion.