Overview
- No other book deals exclusively with the subject of medical image segmentation
- It discusses state-of-the-art techniques, comprising contributions from authors from both industry and academia
Part of the book series: Advances in Computer Vision and Pattern Recognition (ACVPR)
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About this book
This book focuses primarily on state-of-the-art model-based segmentation techniques which are applied to cardiac, brain, breast and microscopic cancer cell imaging. It includes contributions from authors based in both industry and academia and presents a host of new material including algorithms for:
- brain segmentation applied to MR;
- neuro-application using MR;
- parametric and geometric deformable models for brain segmentation;
- left ventricle segmentation and analysis using least squares and constrained least squares models for cardiac X-rays;
- left ventricle analysis in echocardioangiograms;
- breast lesion detection in digital mammograms;
detection of cells in cell images.
As an overview of the latest techniques, this book will be of particular interest to students and researchers in medical engineering, image processing, computer graphics, mathematical modelling and data analysis. It will also be of interest to researchers in the fields of mammography, cardiology, pathology and neurology.
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Keywords
Table of contents (11 chapters)
Editors and Affiliations
Bibliographic Information
Book Title: Advanced Algorithmic Approaches to Medical Image Segmentation
Book Subtitle: State-of-the-Art Applications in Cardiology, Neurology, Mammography and Pathology
Editors: Jasjit S. Suri, S. Kamaledin Setarehdan, Sameer Singh
Series Title: Advances in Computer Vision and Pattern Recognition
DOI: https://doi.org/10.1007/978-0-85729-333-6
Publisher: Springer London
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eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag London 2002
Hardcover ISBN: 978-1-85233-389-8Published: 11 December 2001
Softcover ISBN: 978-1-4471-1043-9Published: 05 September 2012
eBook ISBN: 978-0-85729-333-6Published: 07 September 2012
Series ISSN: 2191-6586
Series E-ISSN: 2191-6594
Edition Number: 1
Number of Pages: XXVII, 636
Topics: Image Processing and Computer Vision, Pattern Recognition, Computer Graphics, Health Informatics, Pathology, Cardiology