Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis

ECCV 2004 Workshops CVAMIA and MMBIA, Prague, Czech Republic, May 15, 2004, Revised Selected Papers

  • Milan Sonka
  • Ioannis A. Kakadiaris
  • Jan Kybic

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3117)

Table of contents

  1. Front Matter
  2. Acquisition Techniques

    1. James F. Greenleaf, Mostafa Fatemi, Marek Belohlavek
      Pages 1-10
    2. Chris Baker, Chris Debrunner, Mohamed Mahfouz, William Hoff, Jamon Bowen
      Pages 11-23
    3. Mai K. Nguyen, T. T. Truong, J. L. Delarbre, N. Kitanine
      Pages 24-34
  3. Reconstruction

  4. Mathematical Methods

    1. A. Suinesiaputra, A. F. Frangi, M. Üzümcü, J. H. C. Reiber, B. P. F. Lelieveldt
      Pages 75-86
    2. Brian Avants, James Gee
      Pages 99-110
    3. Mikaël Rousson, Christophe Lenglet, Rachid Deriche
      Pages 123-134
    4. Lucero Lopez-Perez, Rachid Deriche, Nir Sochen
      Pages 135-144
  5. Medical Image Segmentation

    1. Julien Sénégas, Thomas Netsch, Chris A. Cocosco, Gunnar Lund, Alexander Stork
      Pages 157-168
    2. Maxime Descoteaux, Louis Collins, Kaleem Siddiqi
      Pages 169-180
    3. Eric Berg, Mohamed Mahfouz, Christian Debrunner, William Hoff
      Pages 181-192
    4. Joes Staal, Bram van Ginneken, Max A. Viergever
      Pages 193-204

About these proceedings


Medical imaging and medical image analysisare rapidly developing. While m- ical imaging has already become a standard of modern medical care, medical image analysis is still mostly performed visually and qualitatively. The ev- increasing volume of acquired data makes it impossible to utilize them in full. Equally important, the visual approaches to medical image analysis are known to su?er from a lack of reproducibility. A signi?cant researche?ort is devoted to developing algorithms for processing the wealth of data available and extracting the relevant information in a computerized and quantitative fashion. Medical imaging and image analysis are interdisciplinary areas combining electrical, computer, and biomedical engineering; computer science; mathem- ics; physics; statistics; biology; medicine; and other ?elds. Medical imaging and computer vision, interestingly enough, have developed and continue developing somewhat independently. Nevertheless, bringing them together promises to b- e?t both of these ?elds. We were enthusiastic when the organizers of the 2004 European Conference on Computer Vision (ECCV) allowed us to organize a satellite workshop devoted to medical image analysis.


3 d imaging Computer Vision Image segmentation biomedical engineering biomedical image analysis human genome image analysis mathematical methods in computer vision medical image processing medical imaging mri statistical pattern recognition ultrasound imaging

Editors and affiliations

  • Milan Sonka
    • 1
  • Ioannis A. Kakadiaris
    • 2
  • Jan Kybic
    • 3
  1. 1.Department of Electrical and Computer EngineeringUniversity of IowaIowa CityUSA
  2. 2.Computational Biomedicine LabUniversity of HoustonHouston
  3. 3.Center for Machine PerceptionCzech Technical UniversityPrague 2Czech Republic

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2004
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-22675-8
  • Online ISBN 978-3-540-27816-0
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book
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