Overview
- Addresses the utilization of color information in medical image
- Analysis contains contributions of leading experts in the area
- State-of-the-art in color medical image analysis
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Computational Vision and Biomechanics (LNCVB, volume 6)
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Table of contents (10 chapters)
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Front Matter
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Back Matter
Keywords
About this book
Since the early 20th century, medical imaging has been dominated by monochrome imaging modalities such as x-ray, computed tomography, ultrasound, and magnetic resonance imaging. As a result, color information has been overlooked in medical image analysis applications. Recently, various medical imaging modalities that involve color information have been introduced. These include cervicography, dermoscopy, fundus photography, gastrointestinal endoscopy, microscopy, and wound photography. However, in comparison to monochrome images, the analysis of color images is a relatively unexplored area. The multivariate nature of color image data presents new challenges for researchers and practitioners as the numerous methods developed for monochrome images are often not directly applicable to multichannel images.
The goal of this volume is to summarize the state-of-the-art in the utilization of color information in medical image analysis.
Editors and Affiliations
Bibliographic Information
Book Title: Color Medical Image Analysis
Editors: M. Emre Celebi, Gerald Schaefer
Series Title: Lecture Notes in Computational Vision and Biomechanics
DOI: https://doi.org/10.1007/978-94-007-5389-1
Publisher: Springer Dordrecht
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Science+Business Media Dordrecht 2013
Hardcover ISBN: 978-94-007-5388-4Published: 16 September 2012
Softcover ISBN: 978-94-017-8129-9Published: 15 October 2014
eBook ISBN: 978-94-007-5389-1Published: 16 September 2012
Series ISSN: 2212-9391
Series E-ISSN: 2212-9413
Edition Number: 1
Number of Pages: X, 206
Topics: Biomedical Engineering and Bioengineering, Image Processing and Computer Vision, Imaging / Radiology