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3D Segmentation and Quantification of Human Vessels Based on a New 3D Parametric Intensity Model

  • Stefan Wörz
  • Karl Rohr
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3175)

Abstract

We introduce an approach for 3D segmentation and quantification of vessels. The approach is based on a new 3D cylindrical parametric intensity model, which is directly fit to the image intensities through an incremental process based on a Kalman filter. The model has been successfully applied to segment vessels from 3D MRA images. Our experiments show that the model yields superior results in estimating the vessel radius compared to approaches based on a Gaussian model. Also, we point out general limitations in estimating the radius of thin vessels.

Keywords

Deformable Model Cylindrical Model Vessel Segmentation Thin Vessel Human Vessel 
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 2004

Authors and Affiliations

  • Stefan Wörz
    • 1
  • Karl Rohr
    • 1
  1. 1.School of Information Technology, Computer Vision & Graphics GroupInternational University in GermanyBruchsal

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