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- Title
Blind source separation and automatic tissue typing of microdiffraction data by hierarchical nonnegative matrix factorization.
- Authors
Ladisa, Massimo; Lamura, Antonio; Laudadio, Teresa
- Abstract
In this article a nonnegative blind source separation technique, known as nonnegative matrix factorization, is applied to microdiffraction data in order to extract characteristic patterns and to determine their spatial distribution in tissue typing problems occurring in bone-tissue engineering. In contrast to other blind source separation methods, nonnegative matrix factorization only requires nonnegative constraints on the extracted sources and corresponding weights, which makes it suitable for the analysis of data occurring in a variety of applications. In particular, here nonnegative matrix factorization is hierarchically applied to two-dimensional meshes of X-ray diffraction data measured in bone samples with implanted tissue. Such data are characterized by nonnegative profiles and their analysis provides significant information about the structure of possibly new deposited bone tissue. A simulation and real data studies show that the proposed method is able to retrieve the patterns of interest and to provide a reliable and accurate segmentation of the given X-ray diffraction data.
- Subjects
BLIND source separation; BLIND channel identification (Telecommunications); SIGNAL separation; X-ray diffraction; SPATIAL distribution (Quantum optics); SINGLE photon generation
- Publication
Journal of Applied Crystallography, 2013, Vol 46, Issue 5, p1467
- ISSN
0021-8898
- Publication type
Article
- DOI
10.1107/S0021889813021729