Automatic segmentation of Optic Pathway Gliomas in MRI

L. Weizman*, L. Joskowicz, L. Ben-Sira, R. Precel, D. Ben-Bashat

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

This paper presents an automatic method for the segmentation of Optic Pathway Gliomas (OPGs) from multi-spectral MRI datasets. The method starts with the automatic localization of the OPG and its core with an anatomical tumor atlas followed by a binary voxel classification with a probabilistic tissue model whose parameters are estimated from MR images. The method effectively incorporates prior location, shape, and intensity information to accurately identify the sharp OPG boundaries and to delineate in a consistent and repeatable manner the OPG contours that cannot be clearly distinguished on conventional MR images. Our experimental study on 15 datasets yield a mean surface distance error of 0.67mm and mean volume overlap difference of 28.6% as compared to manual segmentation by an expert radiologist. To the best of our knowledge, this is the first method that addresses automatic OPG segmentation.

Original languageAmerican English
Title of host publication2010 7th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI 2010 - Proceedings
Pages920-923
Number of pages4
DOIs
StatePublished - 2010
Event7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Rotterdam, Netherlands
Duration: 14 Apr 201017 Apr 2010

Publication series

Name2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings

Conference

Conference7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010
Country/TerritoryNetherlands
CityRotterdam
Period14/04/1017/04/10

Keywords

  • Brain tumor
  • Multi-spectral MRI
  • Optic Pathway Glioma
  • Segmentation

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