Segmentation of brain MRI by adaptive mean shift

Arnaldo Mayer*, Hayit Greenspan

*Corresponding author for this work

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

Abstract

A new automatic segmentation method for MRI images of the brain is presented, based on the adaptive mean-shift algorithm. Existing parametric methods utilize the intensity information for the segmentation task. When spatial information is introduced, parametric models may fail due to the non-convex nature of the brain tissue anatomy. A natural integration of intensity and spatial features is enabled in the non-parametric mean-shift formalism. The proposed method is validated on both simulated and real datasets.

Original languageEnglish
Title of host publication2006 3rd IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro - Proceedings
Pages319-322
Number of pages4
StatePublished - 2006
Event2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Arlington, VA, United States
Duration: 6 Apr 20069 Apr 2006

Publication series

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

Conference

Conference2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Country/TerritoryUnited States
CityArlington, VA
Period6/04/069/04/06

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