Classification of Crystallographic Data Using Canonical Correlation Analysis

نویسندگان

  • M. Ladisa
  • Antonio Lamura
  • Teresa Laudadio
چکیده

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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عنوان ژورنال:
  • EURASIP J. Adv. Sig. Proc.

دوره 2007  شماره 

صفحات  -

تاریخ انتشار 2007