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Registration and Segmentation in Medical Imaging

  • Daniel Rueckert
  • Julia A. Schnabel
Part of the Studies in Computational Intelligence book series (SCI, volume 532)

Abstract

The analysis of medical images plays an increasingly important role in many clinical applications. Different imaging modalities often provide complementary anatomical information about the underlying tissues such as the X-ray attenuation coefficients from X-ray computed tomography (CT), and proton density or proton relaxation times from magnetic resonance (MR) imaging. The images allow clinicians to gather information about the size, shape and spatial relationship between anatomical structures and any pathology, if present. Other imaging modalities provide functional information such as the blood flow or glucose metabolism from positron emission tomography (PET) or single-photon emission tomography (SPECT), and permit clinicians to study the relationship between anatomy and physiology. Finally, histological images provide another important source of information which depicts structures at a microscopic level of resolution.

Keywords

Mutual Information Medical Image Control Point Image Registration Target Image 
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 2014

Authors and Affiliations

  1. 1.Biomedical Image Analysis Group, Department of ComputingImperial College LondonLondonUK
  2. 2.Institute of Biomedical Engineering, Department of Engineering ScienceUniversity of OxfordOxfordUK

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