ENGINEERING - Cambridge University Press India

Kernel Methods for
Pattern Analysis
John Shaw-Taylor
University of
Southampton
& Nello Cristianini
University of Bristol
Kernel methods provide a powerful and unified
framework for pattern discovery, motivating
algorithms that can act on general types of data
(e.g. strings, vectors or text) and look for general
types of relations (e.g. rankings, classifications,
regressions, clusters). The application areas range
from neural networks and pattern recognition to
machine learning and data mining. This book,
developed from lectures and tutorials, fulfils two
major roles: firstly it provides practitioners with a
large toolkit of algorithms, kernels and solutions
ready to use for standard pattern discovery
problems in fields such as bioinformatics, text
analysis, image analysis. Secondly it provides an
easy introduction for students and researchers to
the growing field of kernel-based pattern analysis,
demonstrating with examples how to handcraft an
algorithm or a kernel for a new specific
application, and covering all the necessary
conceptual and mathematical tools to do so.
Contents: Preface; Part I Basic Concepts:
1. Pattern analysis; 2. Kernel methods: an
overview; 3. Properties of Kernels; 4. Detecting
stable patterns; Part II Pattern Analysis
Algorithms: 5. Elementary algorithms in feature
space; 6. Pattern analysis using eigendecompositions;
7. Pattern analysis using convex
optimisation; 8. Ranking, clustering and data
visualisation; Part III Constructing Kernels:
9. Basic kernels and kernel types; 10. Kernels for
text.; 11. Kernels for structured data: strings, trees,
etc.; 12. Kernels from generative models; Part IV
Appendices; Appendix A Proof omitted from the
main text; Appendix B Notational conventions;
Appendix C List of pattern analysis methods;
Appendix D List of kernels; Bibliography; Index.
ISBN: 9780521813976 476pp £ 55.00
BIOTECHNOLOGY/ BIOINFORMATICS
Digital Image
Processing for
Medical
Applications
Geoff Dougherty
California State University,
Channel Islands
NEW
Image processing is a hands-on discipline, and
the best way to learn is by doing. This text takes
its motivation from medical applications and uses
real medical images and situations to illustrate and
clarify concepts and to build intuition, insight and
understanding. Designed for advanced
undergraduates and graduate students who will
become end-users of digital image processing, it
covers the basics of the major clinical imaging
modalities, explaining how the images are
produced and acquired. It then presents the
standard image processing operations, focusing
on practical issues and problem solving. Crucially,
the book explains when and why particular
operations are done, and practical computerbased
activities show how these operations affect
real images. All images, links to the public-domain
software ImageJ and custom plug-ins, and
selected solutions are available from
www.cambridge.org/books/dougherty.
Contents: Preface; 1. Introduction; 2. Imaging
systems; 3. Medical images obtained with ionizing
radiation; 4. Medical images obtained with nonionizing
radiation; 5. Fundamentals of digital
image processing; 6. Image enhancement in the
spatial domain; 7. Image enhancement in the
frequency domain; 8. Image restoration;
9. Morphological image processing; 10. Image
segmentation; 11. Feature recognition and
classification; 12. Three-dimensional visualization;
13. Medical applications of imaging; 14. Frontiers
of image processing in medicine; Appendix A. The
Fourier Series and Fourier Transform; Appendix B.
Set theory and probability; Appendix C. Shape and
texture; Bibliography; Index.
ISBN: 9780521181938 462pp ` 695.00
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