A computational framework for ultra-high resolution cortical segmentation at 7 Tesla

Pierre Louis Bazin, Marcel Weiss, Juliane Dinse, Andreas Schäfer, Robert Trampel, Robert Turner

Research output: Contribution to journalReview articlepeer-review

Abstract

This paper presents a computational framework for whole brain segmentation of 7. Tesla magnetic resonance images able to handle ultra-high resolution data. The approach combines multi-object topology-preserving deformable models with shape and intensity atlases to encode prior anatomical knowledge in a computationally efficient algorithm. Experimental validation on simulated and real brain images shows accuracy and robustness of the method and demonstrates the benefits of an increased processing resolution.

Original languageEnglish (US)
Pages (from-to)201-209
Number of pages9
JournalNeuroImage
Volume93
DOIs
StatePublished - Jun 1 2014

Keywords

  • 7 Tesla MRI
  • Ultra-high resolution
  • Whole brain segmentation

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

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