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Segmentation of Multimodality Osteosarcoma MRI with Vectorial Fuzzy-Connectedness Theory

  • Jing Ma
  • Minglu Li
  • Yongqiang Zhao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3614)

Abstract

This paper illustrates an algorithm for osteosarcoma segmentation, using vectorial fuzzy-connectedness segmentation, and coming up with a methodology which can be used to segment some distinct tissues of osteosarcoma such as tumor, necrosis and parosteal sarcoma from 3D vectorial images. However, fuzzy-connectedness segmentation can be successfully used only in connected regions. In this paper, some improvements have been made to segment the interested tissues which are distributed in disconnected regions. And the paper speeds up the process of segmentation by segmenting two osteosarcoma tissues simultaneously. The methology has been applied to a medical image analysis system of osteosarcoma segmentation and 3D reconstruction, which has been put into practical use in some hospitals.

Keywords

Image Segmentation Seed Point Bone Cancer Osteosarcoma Tissue Stir Sequence 
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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References

  1. 1.
    Udupa, J.K., Saha, P.K.: Fuzzy connectedness and image segmentation. In: Proceedings of the IEEE, vol. 91, pp. 1649–1669 (2003)Google Scholar
  2. 2.
    Zhuge, Y., Udupa, J.K., Saha, P.K.: Vectorial scale-based fuzzy connected image segmentation. In: Proceedings of SPIE: Medical Imaging, vol. 4684, pp. 1476–1487 (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Jing Ma
    • 1
  • Minglu Li
    • 1
  • Yongqiang Zhao
    • 1
  1. 1.Department of Computer Science and EngineeringShanghai Jiao Tong UniversityShanghaiChina

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