Here's a first-of-its-kind book that bridges the gap between biomedical imaging and the bioscience community. This unique resource gives you a detailed understanding of imaging platforms, fluorescence imaging, and fundamental image processing algorithms. Further, it guides you through application of advanced image analysis methods and techniques to specific biological problems. The book presents applications that span a wide range of scales, from the detection of signaling events in sub-cellular structures, to the automated analysis of tissue structures. Other critical areas discussed include the dynamics of cell populations and in vivo microscopy. This cutting-edge volume is supported with over 160 illustrations that support key topics throughout the book.
IntroductionIntroduction to Optimal Microscopy. Molecular Imaging Probes. Overview of Image Analysis Methods. Farsight: Mapping Biology into Geometry. Sub-cellular Structures and EventsAutomated Recognition of Patterns Characteristic of Sub-cellular Structures in Fluorescence Microscopy Images. Simulation and Estimation of Fluorescence Microscopy Image Sequences for Intra-cellular Dynamics and Trafficking. Quantum Dots Shed Light on Processes in Living Cells. Protrusion Measurements. ; Structure and Dynamics of Cell PopulationsMethods for High-Content, High-Throughput Image-Based Cell Screening. Automated Cell Tracking Tools for Quantitative Motility Studies. Automated Analysis of Mititic Phases of Human Cells in 3D Fluorescence Microscopy Image Sequences. Spatio-Temporal Cell Cycle Phase Analysis. Cell Segmentation for Division Rate Estimation in Computerized Video Time-Lapse Microscopy. ; Automated Tissue AnalysisImaging Methods for Automated Pathology. Towards Segmentation of Irregular Tubular Structures in 3D Confocal Microscopy Images of Neural Tissue. ; In Vivo MicroscopySmall Critter Imaging. Processing and Mosaicing of Fibered Confocal Images. Conclusion and Summary. ; To view complete TOC:; Click Google Preview button under book title above, then click on Contents tab.;
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Raghu Machiraju
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Jens Rittscher
Jens Rittscher is a research scientist at GE Global Research where he is a member of the Visualization and Computer Vision Lab. He holds a D.Phil. in computer vision from the University of Oxford. Raghu Machiraju is an associate professor in the Department of Computer Science and Engineering at Ohio State University. His main interests are in imaging and visualization as they are applied to biology, medicine and engineering.
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Stephen T.C. Wong
Stephen T.C. Wong is the vice chair and chief of medical physics in the Department of Radiology and the director of the bioinformatics program at The Methodist Hospital Research Institute. He was the founding director of the Center for Bioinformatics, Harvard Center of Neurodegeneration and Repair (HCNR), and an Associate Professor of Radiology, Harvard Medical School and Brigham & Women's Hospital. His research theme has been focused on the application of advanced technology to pragmatic biomedical problems and is based on the belief that problems of importance involve the interplay between theory and application.