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Handbook of Biomedical Image Analysis Volume 1 Segmentation Models Part A 1st Editon 2005 Hardbound at Meripustak

Handbook of Biomedical Image Analysis Volume 1 Segmentation Models Part A 1st Editon 2005 Hardbound by David Wilson, Swamy Laxminarayan, Springer

Books from same Author: David Wilson, Swamy Laxminarayan

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General Information  
Author(s)David Wilson, Swamy Laxminarayan
PublisherSpringer
Edition1st Edition
ISBN9780306485503
Pages648
BindingHardbound
LanguageEnglish
Publish YearJuly 2005

Description

Springer Handbook of Biomedical Image Analysis Volume 1 Segmentation Models Part A 1st Editon 2005 Hardbound by David Wilson, Swamy Laxminarayan

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 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.



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