High Resolution Hippocampus Subfield Segmentation Using Multispectral Multiatlas Patch-Based Label Fusion

  • José E. Romero
  • Pierrick Coupe
  • José V. Manjón
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9993)

Abstract

The hippocampus is a brain structure that is involved in several cognitive functions such as memory and learning. It is a structure of great interest due to its relationship to neurodegenerative processes such as the Alzheimer’s disease. In this work, we propose a novel multispectral multiatlas patch-based method to automatically segment hippocampus subfields using high resolution T1-weighted and T2-weighted magnetic resonance images (MRI). The proposed method works well also on standard resolution images after superresolution and consistently performs better than monospectral version. Finally, the proposed method was compared with similar state-of-the-art methods showing better results in terms of both accuracy and efficiency.

Notes

Acknowledgements

This research was supported by the Spanish grant TIN2013-43457-R from the Ministerio de Economia y competitividad. This study has been carried out with financial support from the French State, managed by the French National Research Agency (ANR) in the frame of the Investments for the future Program IdEx Bordeaux (ANR-10-IDEX-03-02, HL-MRI Project), Cluster of excellence CPU and TRAIL (HR-DTI ANR-10-LABX-57) and the CNRS multidisciplinary project “Défi imag’In”.

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • José E. Romero
    • 1
  • Pierrick Coupe
    • 2
    • 3
  • José V. Manjón
    • 1
  1. 1.Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA)Universitat Politècnica de ValènciaValenciaSpain
  2. 2.University of Bordeaux, LaBRI, UMR 5800, PICTURATalenceFrance
  3. 3.CNRS, LaBRI, UMR 5800, PICTURATalenceFrance

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