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Shape Analysis for Brain Structures

  • Bernard Ng
  • Matthew Toews
  • Stanley Durrleman
  • Yonggang Shi
Chapter
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 14)

Abstract

Advances in magnetic resonance imaging (MRI) have enabled non-invasive examination of brain structures in unprecedented details. With increasing amount of high resolution MRI data becoming available, we are at a position to make significant clinical contributions. In this chapter, we review the main approaches to shape analysis for brain structures. The purpose of this review is to provide methodological insights for pushing forward shape analysis research, so that we can better benefit from the available high resolution data. We describe in this review point-based, mesh-based, function-based, and medial representations as well as deformetrics. Their respective advantages and disadvantages as well as the implications of increasing resolution and greater sample sizes on these shape analysis approaches are discussed.

Keywords

Brain Correspondence Shape representation Statistical analysis 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Bernard Ng
    • 1
    • 2
  • Matthew Toews
    • 3
  • Stanley Durrleman
    • 4
    • 5
  • Yonggang Shi
    • 6
  1. 1.PARIETAL TeamINRIAGif-Sur-YvetteFrance
  2. 2.FIND LabStanford UniversityStanfordUSA
  3. 3.Surgical Planning Laboratory, Brigham and Women’s HospitalHarvard Medical SchoolBostonUSA
  4. 4.ARAMIS TeamINRIAParisFrance
  5. 5.Institut du Cerveau et de la Moëlle épinière (ICM)Hôpital de la Pitié SalpêtrièreParisFrance
  6. 6.Institute for Neuroimaging and Informatics, Keck School of MedicineUniversity of Southern CaliforniaLosAngelesUSA

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