Biomedical Imaging: A Computer Vision Perspective

  • Xiaoyi Jiang
  • Mohammad Dawood
  • Fabian Gigengack
  • Benjamin Risse
  • Sönke Schmid
  • Daniel Tenbrinck
  • Klaus Schäfers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8047)


Many computer vision algorithms have been successfully adapted and applied to biomedical imaging applications. However, biomedical computer vision is far beyond being only an application field. Indeed, it is a wide field with huge potential for developing novel concepts and algorithms and can be seen as a driving force for computer vision research. To emphasize this view of biomedical computer vision we consider a variety of important topics of biomedical imaging in this paper and exemplarily discuss some challenges, the related concepts, techniques, and algorithms.


Positron Emission Tomography Positron Emission Tomography Imaging Motion Estimation Image Registration Biomedical Imaging 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Xiaoyi Jiang
    • 1
    • 2
    • 3
  • Mohammad Dawood
    • 1
    • 2
  • Fabian Gigengack
    • 1
    • 2
  • Benjamin Risse
    • 1
    • 4
  • Sönke Schmid
    • 1
    • 2
    • 3
  • Daniel Tenbrinck
    • 1
    • 2
  • Klaus Schäfers
    • 2
    • 3
  1. 1.Department of Mathematics and Computer ScienceUniversity of MünsterGermany
  2. 2.European Institute for Molecular Imaging (EIMI)University of MünsterGermany
  3. 3.Cluster of Excellence EXC 1003, Cells in Motion, CiMMünsterGermany
  4. 4.Department of Neuro and Behavioral BiologyUniversity of MünsterGermany

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