Mammographic Image Analysis

  • Ralph Highnam
  • Michael Brady

Part of the Computational Imaging and Vision book series (CIVI, volume 14)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. Ralph Highnam, Michael Brady
      Pages 1-27
  3. Generating h int

    1. Front Matter
      Pages 29-29
    2. Ralph Highnam, Michael Brady
      Pages 31-55
    3. Ralph Highnam, Michael Brady
      Pages 57-76
    4. Ralph Highnam, Michael Brady
      Pages 77-89
    5. Ralph Highnam, Michael Brady
      Pages 91-102
    6. Ralph Highnam, Michael Brady
      Pages 103-120
  4. Exploiting The h int Model

    1. Front Matter
      Pages 121-121
    2. Ralph Highnam, Michael Brady
      Pages 123-142
    3. Ralph Highnam, Michael Brady
      Pages 143-150
    4. Ralph Highnam, Michael Brady
      Pages 151-174
    5. Ralph Highnam, Michael Brady
      Pages 175-190
    6. Ralph Highnam, Michael Brady
      Pages 191-223
    7. Ralph Highnam, Michael Brady
      Pages 225-250
    8. Ralph Highnam, Michael Brady
      Pages 251-284
  5. Further Breast Image Analysis

    1. Front Matter
      Pages 285-285
    2. Ralph Highnam, Michael Brady
      Pages 287-331
    3. Ralph Highnam, Michael Brady
      Pages 333-356

About this book

Introduction

Breast cancer is a major health problem in the Western world, where it is the most common cancer among women. Approximately 1 in 12 women will develop breast cancer during the course of their lives. Over the past twenty years there have been a series of major advances in the manage­ ment of women with breast cancer, ranging from novel chemotherapy and radiotherapy treatments to conservative surgery. The next twenty years are likely to see computerized image analysis playing an increasingly important role in patient management. As applications of image analysis go, medical applications are tough in general, and breast cancer image analysis is one of the toughest. There are many reasons for this: highly variable and irregular shapes of the objects of interest, changing imaging conditions, and the densely textured nature of the images. Add to this the increasing need for quantitative informa­ tion, precision, and reliability (very few false positives), and the image pro­ cessing challenge becomes quite daunting, in fact it pushes image analysis techniques right to their limits.

Keywords

X-ray algorithms image analysis imaging magnetic resonance imaging (MRI) mammography radiation

Authors and affiliations

  • Ralph Highnam
    • 1
  • Michael Brady
    • 1
  1. 1.Department of Engineering ScienceOxford UniversityOxfordUK

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-011-4613-5
  • Copyright Information Kluwer Academic Publishers 1999
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-94-010-5949-7
  • Online ISBN 978-94-011-4613-5
  • Series Print ISSN 1381-6446
  • About this book