biomedical image analysis segmentation (26 Ergebnisse)

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The sequel to the popular lecture book entitled Biomedical Image Analysis: Tracking, this book on Biomedical Image Analysis: Segmentation tackles the challenging task of segmenting biological and medical images. The problem of partitioning multidimensional biomedical data into meaningful regions is perhaps the main roadblock in the automation of biomedical image analysis. Whether the modality of choice is MRI, PET, ultrasound, SPECT, CT, or one of a myriad of microscopy platforms, image segmentation is a vital step in analyzing the constituent biological or medical targets. This book provides a state-of-the-art, comprehensive look at biomedical image segmentation that is accessible to well-equipped undergraduates, graduate students, and research professionals in the biology, biomedical, medical, and engineering fields. Active model methods that have emerged in the last few years are a focus of the book, including parametric active contour and active surface models, active shape models,and geometric active contours that adapt to the image topology. Additionally, Biomedical Image Analysis: Segmentation details attractive new methods that use graph theory in segmentation of biomedical imagery. Finally, the use of exciting new scale space tools in biomedical image analysis is reported. Table of Contents: Introduction / Parametric Active Contours / Active Contours in a Bayesian Framework / Geometric Active Contours / Segmentation with Graph Algorithms / Scale-Space Image Filtering for Segmentation.

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Taschenbuch. Zustand: Neu. Neuware - Handbook of Biomedical Image Analysis: Segmentation Models (Volume II) is dedicated to the segmentation of complex shapes from the field of imaging sciences using different mathematicaltechniques. 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:--- Model-based brain tissue classification--- Supervised texture classification for intravascular tissue characterization--- Medical image segmentation: methods and applications in functional imaging--- Automatic segmentation of pancreatic tumors in CT--- Computerized analysis and vasodilation parameterization in flow-mediated dilation tests from ultrasonic image sequences--- Adaptive approaches to optical segmentation in brain MRI Images--- Automatic analysis of color fundus photographs and its application to the diagnosis of diabetic retinopathy--- Segmentation issues of carotid plaque analysis in MRI--- Accurate lumen identification, detection, and quantification in MR plaque volumes--- Hessian-based multiscale enhancement, description, and quantification of second-order 3D local structures from medical volume data--- A knowledge-based scheme for digital mammography--- Simultaneous fuzzy segmentation--- CAD of mammographic calicification: impact of segmentationAbout 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.

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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

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Softcover. Zustand: New. Zustand des Schutzumschlags: no dj. First. Computer Vision in Biomedical Image Analysis and Segmentation' is a groundbreaking exploration of the rapidly evolving field of computer vision, as applied to biomedical image analysis and segmentation. This comprehensive resource provides a thorough examination of the latest techniques and methodologies, including deep learning, convolutional neural networks, and image processing algorithms. By examining the intersection of computer vision and biomedical imaging, the book sheds new light on the potential of computer vision to revolutionize medical diagnosis, treatment, and research. With its focus on practical applications and real-world examples, 'Computer Vision in Biomedical Image Analysis and Segmentation' is an essential resource for researchers, clinicians, and engineers working at the forefront of this exciting field. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

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