Classification of Crystallographic Data Using Canonical Correlation Analysis. (30th April 2007)

• Record Type: Journal Article
• Authors: Ladisa Ladisa, M. M.; Lamura Lamura, A. A.; Laudadio Laudadio, T. T.
• Other Names: Van Huffel Van Huffel Sabine Sabine Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2007(2007)
• Publication Date: 2007-04-30
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2007/19260
• Languages: English
• ISSNs: 1687-6172

Abstract

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.