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International Conference Image Analysis and Recognition

ICIAR 2004: Image Analysis and Recognition pp 116–123Cite as

Isosurface-Based Level Set Framework for MRA Segmentation

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3212))

Abstract

Segmentation is one of the most important and difficult procedures in medical image analysis and in its clinical applications; and blood vessels are especially difficult to segment. In this paper, we propose an isosurface-based level set framework to extract vasculature tree from magnetic resonance angiography(MRA) volumes. First, we process the extracted isosurface of MRA via the surface normal vectors; then use canny edge detection to compute image-based speed function for level set evolution to refine the processed isosurface for the exact segmentation. Results on cases demonstrate it is the mostly accuracy and efficiency of the approach.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai, China

    Yongqiang Zhao & Minglu Li

Authors
  1. Yongqiang Zhao
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  2. Minglu Li
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Editor information

Editors and Affiliations

  1. FEUP - Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio Campilho

  2. Electrical and Computer Engineering Department, University of Waterloo,  

    Mohamed Kamel

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© 2004 Springer-Verlag Berlin Heidelberg

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Zhao, Y., Li, M. (2004). Isosurface-Based Level Set Framework for MRA Segmentation. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30126-4_15

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  • DOI: https://doi.org/10.1007/978-3-540-30126-4_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23240-7

  • Online ISBN: 978-3-540-30126-4

  • eBook Packages: Springer Book Archive

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