Limits on estimating the width of thin tubular structures in 3d images

  • Authors:
  • Stefan Wörz;Karl Rohr

  • Affiliations:
  • Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, IPMB, and DKFZ Heidelberg, Heidelberg, Germany;Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, IPMB, and DKFZ Heidelberg, Heidelberg, Germany

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

Quantified Score

Hi-index 0.00

Visualization

Abstract

This work studies limits on estimating the width of thin tubular structures in 3D images. Based on nonlinear estimation theory we analyze the minimal stochastic error of estimating the width. Given a 3D analytic model of the image intensities of tubular structures, we derive a closed-form expression for the Cramér-Rao bound of the width estimate under image noise. We use the derived lower bound as a benchmark and compare it with three previously proposed accuracy limits for vessel width estimation. Moreover, by experimental investigations we demonstrate that the derived lower bound can be achieved by fitting a 3D parametric intensity model directly to the image data.