Suri, Jasjit S.

Handbook of Biomedical Image Analysis Volume I: Segmentation Models Part A / [electronic resource] : edited by Jasjit S. Suri, David L. Wilson, Swamy Laxminarayan. - Boston, MA : Springer US, 2005. - XVIII, 648 p. With CD-ROM online resource. - International Topics in Biomedical Engineering . - International Topics in Biomedical Engineering .

A Basic Model for IVUS Image Simulation -- Quantitative Functional Imaging with Positron Emission Tomography: Principles and Instrumentation -- Advances in Magnetic Resonance Angiography and Physical Principles -- Recent Advances in the Level Set Method -- Shape From Shading Models -- Wavelets in Medical Image Processing: Denoising, Segmentation, and Registration -- Improving the Initialization, Convergence, and Memory Utilization for Deformable Models -- Level Set Segmentation of Biological Volume Datasets -- Advanced Segmentation Techniques -- A Region-Aided Color Geometric Snake -- Co-Volume Level Set Method in Subjective Surface Based Medical Image Segmentation.

Handbook of Biomedical Image Analysis: Segmentation Models (Volume I) is dedicated to the segmentation of complex shapes from the field of imaging sciences using different mathematical techniques. This volume is aimed at researchers and educators in imaging sciences, radiological imaging, clinical and diagnostic imaging, physicists covering different medical imaging modalities, as well as researchers in biomedical engineering, applied mathematics, algorithmic development, computer vision, signal processing, computer graphics and multimedia in general, both in academia and industry . Key Features: - Principles of intra-vascular ultrasound (IVUS) - Principles of positron emission tomography (PET) - Physical principles of magnetic resonance angiography (MRA). - Basic and advanced level set methods - Shape for shading method for medical image analysis - Wavelet transforms and other multi-scale analysis functions - Three dimensional deformable surfaces - Level Set application for CT lungs, brain MRI and MRA volume segmentation - Segmentation of incomplete tomographic medical data sets - Subjective level sets for missing boundaries for segmentation About the Editors: Jasjit Suri, Ph.D. has spent over 20 years in the field of computer and electrical engineering, and more than a decade in imaging sciences. Dr. Suri has a masters degree in computer sciences from the University of Illinois and a doctorate in Electrical Engineering from the University of Washington, Seattle. Dr. Suri has published over 125 technical publications in medical imaging, as well as being a senior member of IEEE and a member of the engineering honor societies Eta-Kappa-Nu and Tau-Beta-Phi, and a recipient of the President's Gold Medal in 1980. He is also a fellow of American Institute of Medical and Biological Engineering. David Wilson, Ph D. is a Professor of Biomedical Engineering and Radiology at Case Western Reserve University, having gained his doctorate from Rice University. He has over 60 refereed journal publications and is co-owner of several patents. Professor Wilson has actively developed biomedical imaging at CWRU. He has led a faculty recruitment effort, and he has served as PI or has been an active leader on multiple research and equipment developmental awards given to CWRU, including an NIH planning grant award for an in vivo Cellular and Molecular Imaging Center and an Ohio Wright Center of Innovation award. Swamy Laxminarayan, Dsc championed the field of Biomedical Engineering for over 30 years, having held a variety of senior positions within the industry. He is an internationally recognized scientist, engineer, and educator and has been published in over 200 technical publications in biomedical information technology, computation biology, signal and image processing, biotechnology, and physiological system modeling. Prof. Laxminarayan is a fellow of AIMBE and a recipient of IEEE 3rd Millennium Medal.


10.1007/b104805 doi

Radiology, Medical.
Information theory.
Computer graphics.
Computer vision.
Biomedical engineering.
Biomedical Engineering.
Imaging / Radiology.
Theory of Computation.
Computer Graphics.
Image Processing and Computer Vision.



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