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Extending Local Binary Patterns to 3D for the diagnosis of Alzheimer's disease

Authors: Pedro Morgado, Margarida Silveira and Jorge Salvador Marques Published at: International Symposium on Biomedical Imaging (ISBI), San Francisco. Publication type: Conference Proceedings Publication date: April, 2013.

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Abstract

Neuroimaging has shown great potential for the computer-aided diagnosis (CAD) of both Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI). However, the texture of such images has been little explored. In this paper, we explore the discriminative power of the Local Binary Patterns (LBPs) texture descriptor to diagnose AD and MCI from 3D brain images. For this purpose, we propose a novel extension of LBPs to full 3D data that, unlike previous approaches, makes no approximations to the underlying concepts of uniformity and rotation invariance. Experimental results obtained using FDG-PET images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) showed that the new feature was able to improve the system's performance when compared to the raw Voxel Intensities (VI) and to the standard 2D LBP version applied to axial cuts of the PET volume.

Citation

@inproceedings{Morgado:ISBI2013b,
  title={Extending Local Binary Patterns to 3D for the diagnosis of Alzheimer's disease},
  author={Morgado, Pedro M and Silveira, Margarida and Marques, Jorge S},
  booktitle={IEEE 10th International Symposium on Biomedical Imaging},
  year={2013}
}

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