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Classification of Crystallographic Data Using Canonical Correlation Analysis

Abstract

A reliable and automatic method is applied to crystallographic data for tissue typing. The technique is based on canonical correlation analysis, a statistical method which makes use of the spectral-spatial information characterizing X-ray diffraction data measured from bone samples with implanted tissues. The performance has been compared with a standard crystallographic technique in terms of accuracy and automation. The proposed approach is able to provide reliable tissue classification with a direct tissue visualization without requiring any user interaction.

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Correspondence to M. Ladisa.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://doi.org/creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Ladisa, M., Lamura, A. & Laudadio, T. Classification of Crystallographic Data Using Canonical Correlation Analysis. EURASIP J. Adv. Signal Process. 2007, 019260 (2007). https://doi.org/10.1155/2007/19260

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Keywords

  • Statistical Method
  • Information Technology
  • Diffraction Data
  • Quantum Information
  • Crystallographic Data