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Robust Active Shape Models: A Robust, Generic and Simple Automatic Segmentation Tool

  • Julien Abi-Nahed
  • Marie-Pierre Jolly
  • Guang-Zhong Yang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)

Abstract

This paper presents a new segmentation algorithm which combines active shape model and robust point matching techniques. It can use any simple feature detector to extract a large number of feature points in the image. Robust point matching is then used to search for the correspondences between feature and model points while the model is being deformed along the modes of variation of the active shape model. Although the algorithm is generic, it is particularly suited for medical imaging applications where prior knowledge is available. The value of the proposed method is examined with two different medical imaging modalities (Ultrasound, MRI) and in both 2D and 3D. The experiments have shown that the proposed algorithm is immune to missing feature points and noise. It has demonstrated significant improvements when compared to RPM-TPS and ASM alone.

Keywords

Feature Point Right Ventricle Model Point Active Appearance Model Active Shape Model 
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 2006

Authors and Affiliations

  • Julien Abi-Nahed
    • 1
    • 2
  • Marie-Pierre Jolly
    • 1
  • Guang-Zhong Yang
    • 2
  1. 1.Imaging and Visualization DepartmentSiemens Corporate ResearchPrincetonUSA
  2. 2.Royal Society/Wolfson Foundation Medical Image Computing LaboratoryImperial College LondonLondonUK

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