Segmentation of neck lymph nodes in CT datasets with stable 3d mass-spring models

  • Authors:

  • Jana Dornheim;Heiko Seim;Bernhard Preim;Ilka Hertel;Gero Strauss

  • Affiliations:

  • Otto-von-Guericke-Universität Magdeburg, Germany;Otto-von-Guericke-Universität Magdeburg, Germany;Otto-von-Guericke-Universität Magdeburg, Germany;Hals-Nasen-Ohren-Universitätsklinik Leipzig, Germany;Hals-Nasen-Ohren-Universitätsklinik Leipzig, Germany

  • Venue:
  • MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
  • Year:
  • 2006

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Abstract

The quantitative assessment of neck lymph nodes in the context of malign tumors requires an efficient segmentation technique for lymph nodes in tomographic 3D datasets. We present a Stable 3D Mass-Spring Model for lymph node segmentation in CT datasets. Our model for the first time represents concurrently the characteristic gray value range, directed contour information as well as shape knowledge, which leads to a much more robust and efficient segmentation process. Our model design and segmentation accuracy are both evaluated with lymph nodes from clinical CT neck datasets.