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Classification of Crystallographic Data Using Canonical Correlation Analysis

EURASIP Journal on Advances in Signal Processing volume 2007, Article number: 019260 (2007) Cite this article

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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Authors and Affiliations

  1. Istituto di Cristallografia (IC), CNR, Via Amendola 122/O, Bari, 70126, Italy

    M. Ladisa

  2. Istituto Applicazioni Calcolo (IAC), CNR, Via Amendola 122/D, Bari, 70126, Italy

    A. Lamura & T. Laudadio

Authors
  1. M. Ladisa
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  2. A. Lamura
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  3. T. Laudadio
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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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  • DOI: https://doi.org/10.1155/2007/19260

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