Skip to main content
Article thumbnail
Location of Repository

Multilevel Segmentation and Integrated Bayesian Model Classification with an Application to Brain Tumor Segmentation

By Jason J. Corso, Eitan Sharon and Alan Yuille

Abstract

We present a new method for automatic segmentation of heterogeneous image data, which is very common in medical image analysis. The main contribution of the paper is a mathematical formulation for incorporating soft model assignments into the calculation of affinities, which are traditionally model free. We integrate the resulting modelaware affinities into the multilevel segmentation by weighted aggregation algorithm. We apply the technique to the task of detecting and segmenting brain tumor and edema in multimodal MR volumes. Our results indicate the benefit of incorporating model-aware affinities into the segmentation process for the difficult case of brain tumor

Year: 2006
OAI identifier: oai:CiteSeerX.psu:10.1.1.134.9877
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://www.cse.buffalo.edu/~jc... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.