Abstract

Previous clinical research studies consider the existence of differences among normal individual cerebral cortex and show that some features such as cerebral sulci are unique for each individual so that human brains are anatomically different and unique to each individual. In this work, we highlight the idea which consists in using medical data, such as brain MRI images for the purpose of individual identification or verification. In other words, we raise the following question: can one identify individuals using their brain geometry characteristics? Our aim is to validate the feasibility of this new biometrics tool based on human brain characterization. The proposed approach differs from existent biometrics modalities (e.g. fingerprint, hand, etc.) in the sense that brain features cannot be modified by individuals as it is the case when using fake fingerprints, or fake hands. In this work, we consider volumetric Magnetic Resonance Images (MRI) from which brain shapes are extracted using a 3D level-sets segmentation approach. Afterwards, geometrical descriptors are extracted from the 3D brain volume and from a projected version which provide specific features such as the isoperimetric ratio, the cortical surface curvature and the Gyrification index. Evaluations performed on a set of MRI images obtained from (MeDEISA) database show that it is possible to distinguish between individuals using their brain characteristics. Preliminary results are particularly encouraging.

Highlights

  • From a macroscopic point of view, the brain requires various phases during its evolution up to the maturation

  • Previous clinical research studies consider the existence of differences among normal individual cerebral cortex and show that some features such as cerebral sulci are unique for each individual so that human brains are anatomically different and unique to each individual

  • This paper is organized as follows: in Section 2, we present the kernel of our method which consists in: 1) segmenting 3D Magnetic Resonance Images (MRI) images using a level-set based method in order to extract the brain geometry, 2) estimating brain features “geometrical descriptors” from a 3D representation, 3) estimating brain features from a projected representation providing, coronal, axial and sagittal views

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Summary

Introduction

From a macroscopic point of view, the brain requires various phases during its evolution up to the maturation (from a totally smooth brain to a highly wrinkled brain [1, 2]). Studies have shown that the two hemispheres of a same individual are not necessarily symmetrical and that inter-hemispheric variability show that the geometric shape of the cerebral cortex is unique for each individual [4,5,6]. In such a context, we believe that an objective quantification of human brains could contribute considerably in biomedical and biometrics research areas so that one can provide a new useful tool to identify individuals through their cerebral signatures. This approach can be employed for the purpose of cadaver identification, obviously under some specific body conservation conditions and before using any DNA identification

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