BrainPrint : Identifying Subjects by Their Brain

  • Christian Wachinger
  • Polina Golland
  • Martin Reuter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8675)

Abstract

Introducing BrainPrint, a compact and discriminative representation of anatomical structures in the brain. BrainPrint captures shape information of an ensemble of cortical and subcortical structures by solving the 2D and 3D Laplace-Beltrami operator on triangular (boundary) and tetrahedral (volumetric) meshes. We derive a robust classifier for this representation that identifies the subject in a new scan, based on a database of brain scans. In an example dataset containing over 3000 MRI scans, we show that BrainPrint captures unique information about the subject’s anatomy and permits to correctly classify a scan with an accuracy of over 99.8%. All processing steps for obtaining the compact representation are fully automated making this processing framework particularly attractive for handling large datasets.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Christian Wachinger
    • 1
    • 2
  • Polina Golland
    • 1
  • Martin Reuter
    • 1
    • 2
  1. 1.Computer Science and Artificial Intelligence LabMITCambridgeUS
  2. 2.Harvard Medical SchoolMassachusetts General HospitalBostonUS

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