Patch-Based Segmentation from MP2RAGE Images: Comparison to Conventional Techniques

  • Erhard T. Næss-Schmidt
  • Anna Tietze
  • Irene K. Mikkelsen
  • Mikkel Petersen
  • Jakob U. Blicher
  • Pierrick Coupé
  • José V. Manjón
  • Simon F. EskildsenEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9467)


In structural and functional MRI studies there is a need for robust and accurate automatic segmentation of various brain structures. We present a comparison study of three automatic segmentation methods based on the new T1-weighted MR sequence called MP2RAGE, which has superior soft tissue contrast. Automatic segmentations of the thalamus and hippocampus are compared to manual segmentations. In addition, we qualitatively evaluate the segmentations when warped to co-registered maps of the fractional anisotropy (FA) of water diffusion. Compared to manual segmentation, the best results were obtained with a patch-based segmentation method (volBrain) using a library of images from the same scanner (local), followed by volBrain using an external library (external), FSL and Freesurfer. The qualitative evaluation showed that volBrain local and volBrain external produced almost no segmentation errors when overlaid on FA maps, while both FSL and Freesurfer segmentations were found to overlap with white matter tracts. These results underline the importance of applying accurate and robust segmentation methods and demonstrate the superiority of patch-based methods over more conventional methods.


Patch-based segmentation MRI volBrain Freesurfer FSL MP2RAGE 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Erhard T. Næss-Schmidt
    • 1
    • 2
  • Anna Tietze
    • 1
    • 3
  • Irene K. Mikkelsen
    • 1
  • Mikkel Petersen
    • 1
  • Jakob U. Blicher
    • 1
    • 4
  • Pierrick Coupé
    • 5
  • José V. Manjón
    • 6
  • Simon F. Eskildsen
    • 1
    Email author
  1. 1.Center of Functionally Integrative NeuroscienceAarhus UniversityAarhusDenmark
  2. 2.Hammel Neurorehabilitation CentreAarhus UniversityAarhusDenmark
  3. 3.Department of NeuroradiologyAarhus University HospitalAarhusDenmark
  4. 4.Department of NeurologyAarhus University HospitalAarhusDenmark
  5. 5.Laboratoire Bordelais de Recherche en Informatique, PICTURA Research GroupUnité Mixte de Recherche CNRS (UMR 5800)TalencecedexFrance
  6. 6.Instituto de Aplicaciones de las Tecnologías de la Información y de las ComunicacionesAvanzadas (ITACA)Universitat Politècnica de ValènciaValenciaSpain

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