Handbook of biomedical imaging [electronic resource] : methodolgoies and clinical research / Nikos Paragios, James Duncan, Nicholas Ayache, editors.
Paragios, Nikos, editor.; Duncan, James, editor.; Ayache, Nicholas, editor.
2015
RC78.7.D53 H35 2015eb
Available Online

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Title
Handbook of biomedical imaging [electronic resource] : methodolgoies and clinical research / Nikos Paragios, James Duncan, Nicholas Ayache, editors.
ISBN
9780387097497 electronic book
038709749X electronic book
9780387097480
DOI
https://doi.org/10.1007/978-0-387-09749-7
Published
New York : Springer, [2015]
Copyright
©2015
Language
English
Description
1 online resource (vii, 511 pages)
Item Number
10.1007/978-0-387-09749-7 doi
Call Number
RC78.7.D53 H35 2015eb
Dewey Decimal Classification
616.07/54
Summary
Biomedical image analysis has become a major aspect of engineering sciences, and radiology in particular has become a dominant player in the field. Recent developments have made it possible to use biomedical imaging to view the human body from an anatomical or physiological perspective in a non-invasive fashion. Computer-aided diagnosis consists of developing algorithms and intelligent software components that can automatically process images and spot potential irregularities in the health chain. This book explains the process of computer assisted biomedical image analysis diagnosis through mathematical modeling and inference of image-based bio-markers. It covers five crucial thematic areas: methodologies, statistical and physiological models, biomedical perception, clinical biomarkers, and emerging modalities and domains. The dominant state-of-the-art methodologies for content extraction and interpretation of medical images include fuzzy methods, level set methods, kernel methods, and geometric deformable models. The models and techniques discussed are used in the diagnosis, planning, control and follow-up of medical procedures. Throughout the book, challenges and limitations are explored along with new research directions. This complete volume is an exceptional tool for radiologists, research scientists, senior undergraduate and graduate students in health sciences and engineering, and university professors. This book offers a unique guide to the entire chain of biomedical imaging, explaining how image formation is done, and how the most appropriate algorithms are used to address demands and diagnoses.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Description based on print version record.
Added Author
Paragios, Nikos, editor.
Duncan, James, editor.
Ayache, Nicholas, editor.
Available in Other Form
Handbook of biomedical imaging
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Object Segmentation and Markov Random Fields
Fuzzy methods in medical imaging
Curve Propagation, Level Set Methods and Grouping
Kernel Methods in Medical Imaging
Geometric Deformable Models: Overview and Recent Developments
Active Shape and Appearance Models
Statistical Atlases
Statistical Computing on Non-Linear Spaces for Computational Anatomy
Building Patient-Specific Physical and Physiological Computational Models from Medical Images
Constructing a Patient-Specific Model Heart from CT Data
Image-based haemodynamics simulation in intracranial aneursyms
Atlas-based Segmentation
Integration of Topological Constraints in Medical Image Segmentation
Monte Carlo Sampling for the Segmentation of Tubular Structures
Non-rigid registration using free-form deformations
Image registration using mutual information
Physical Model Based Recovery of Displacement and Deformations from 3D medical images
Cardiovascular Informatics
Rheumatoid Arthritis Quantifiction using Appearance Models
Medical Image Processing for Analysis of Colon Motility
Segmentation of Diseased Livers: A 3D Refinement Approach
Intra and inter subject analyses of brain functional Magnetic Resonance Images (fMRI)
Diffusion Tensor Estimation, Regularization and Classification
From Local Q-Ball Estimation to Fibre Crossing Tractography
Segmentation of clustered cells in microscopy images by geometric PDEs and level sets
Atlas-based whole-body registration in mice.

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