BrainPrint: identifying subjects by their brain
Author(s)Wachinger, Christian; Golland, Polina; Reuter, Klaus Martin
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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.
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8675).
DepartmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Lecture Notes in Computer Science
Wachinger, Christian et al. "BrainPrint: identifying subjects by their brain."International Conference on Medical Image Computing and Computer-Assisted Intervention,Lecture Notes in Computer Science 8675, Springer International Publishing, 2014, 41-48. © 2014 Springer International Publishing
Author's final manuscript