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. 2014 Jun:93 Pt 2:201-9.
doi: 10.1016/j.neuroimage.2013.03.077. Epub 2013 Apr 25.

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

Pierre-Louis Bazin  1 , Marcel Weiss  2 , Juliane Dinse  2 , Andreas Schäfer  2 , Robert Trampel  2 , Robert Turner  2
Affiliations

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

Pierre-Louis Bazin et al. Neuroimage. 2014 Jun.

Abstract

This paper presents a computational framework for whole brain segmentation of 7Tesla 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.

Keywords: 7Tesla MRI; Ultra-high resolution; Whole brain segmentation.

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