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BrainPrint: Identifying Subjects by Their Brain

Author(s)
Wachinger, Christian; Golland, Polina; Reuter, Martin
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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.
Date issued
2014
URI
http://hdl.handle.net/1721.1/100260
Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Journal
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014
Publisher
Springer-Verlag
Citation
Wachinger, Christian, Polina Golland, and Martin Reuter. “BrainPrint : Identifying Subjects by Their Brain.” Lecture Notes in Computer Science (2014): 41–48.
Version: Author's final manuscript
ISBN
978-3-319-10442-3
978-3-319-10443-0
ISSN
0302-9743
1611-3349

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