MR Image Segmentation Using Phase Information and a Novel Multiscale Scheme

  • Pierrick Bourgeat
  • Jurgen Fripp
  • Peter Stanwell
  • Saadallah Ramadan
  • Sébastien Ourselin
Conference paper

DOI: 10.1007/11866763_113

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)
Cite this paper as:
Bourgeat P., Fripp J., Stanwell P., Ramadan S., Ourselin S. (2006) MR Image Segmentation Using Phase Information and a Novel Multiscale Scheme. In: Larsen R., Nielsen M., Sporring J. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006. MICCAI 2006. Lecture Notes in Computer Science, vol 4191. Springer, Berlin, Heidelberg

Abstract

This paper considers the problem of automatic classification of textured tissues in 3D MRI. More specifically, it aims at validating the use of features extracted from the phase of the MR signal to improve texture discrimination in bone segmentation. This extra information provides better segmentation, compared to using magnitude only features. We also present a novel multiscale scheme to improve the speed of pixel based classification algorithm, such as support vector machines. This algorithm dramatically increases the speed of the segmentation process by an order of magnitude through a reduction of the number of pixels that needs to be classified in the image.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Pierrick Bourgeat
    • 1
  • Jurgen Fripp
    • 1
    • 3
  • Peter Stanwell
    • 2
  • Saadallah Ramadan
    • 2
  • Sébastien Ourselin
    • 1
  1. 1.BioMedIA Lab, Autonomous Systems LaboratoryCSIRO ICT CentreSydneyAustralia
  2. 2.Institute for Magnetic Resonance ResearchSydneyAustralia
  3. 3.School of ITEEUniversity of QueenslandAustralia

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