Improved segmentation of focal cortical dysplasia lesions on MRI using expansion towards cortical boundaries

O. Colliot*, T. Mansi, P. Besson, N. Bernasconi, A. Bernasconi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Focal cortical dysplasia (FCD), a malformation of cortical development, is an important cause of intractable epilepsy. On Magnetic Resonance Images (MRI), FCD lesions are difficult to distinguish from healthy cortex and defining their spatial extent is challenging. We previously introduced a method to segment FCD lesions on MRI, relying on a 3D deformable model driven by MR features of FCD. In the present paper, we propose to improve our approach by adding a second evolution step which expands the result towards the cortical boundaries. A quantitative evaluation was performed in 18 FCD patients by comparison with manually traced lesion labels. The proposed approach achieved a strong agreement with the manual labels and substantially improved the results obtained with our previous method.

Original languageEnglish (US)
Title of host publication2006 3rd IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro - Proceedings
Pages323-326
Number of pages4
StatePublished - 2006
Externally publishedYes
Event2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Arlington, VA, United States
Duration: Apr 6 2006Apr 9 2006

Publication series

Name2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings
Volume2006

Other

Other2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Country/TerritoryUnited States
CityArlington, VA
Period4/6/064/9/06

ASJC Scopus subject areas

  • General Engineering

Fingerprint

Dive into the research topics of 'Improved segmentation of focal cortical dysplasia lesions on MRI using expansion towards cortical boundaries'. Together they form a unique fingerprint.

Cite this