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Classification of Crystallographic Data Using Canonical Correlation Analysis

Academic Article
Publication Date:
2007
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.
Iris type:
01.01 Articolo in rivista
List of contributors:
Laudadio, Teresa; Ladisa, Massimo; Lamura, Antonio
Authors of the University:
LADISA MASSIMO
LAMURA ANTONIO
LAUDADIO TERESA
Handle:
https://iris.cnr.it/handle/20.500.14243/162539
Published in:
EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING
Journal
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