Published December 16, 2013 | Version v1
Journal article

Imaging regenerating bone tissue based on neural networks applied to micro-diffraction measurements

  • 1. Institute of Crystallography, CNR, via Salaria Km 29.300, I-00015, Monterotondo Roma (Italy)
  • 2. Centro Fermi -Museo Storico della Fisica e Centro Studi e Ricerche 'Enrico Fermi', Roma (Italy)
  • 3. Deutsches Elektronen-Synchrotron DESY, Notkestraße 85, D-22607 Hamburg (Germany)
  • 4. European Synchrotron Radiation Facility, B. P. 220, F-38043 Grenoble Cedex (France)
  • 5. Istituto Nazionale per la Ricerca sul Cancro, and Dipartimento di Medicina Sperimentale dell'Università di Genova and AUO San Martino Istituto Nazionale per la Ricerca sul Cancro, Largo R. Benzi 10, 16132, Genova (Italy)
  • 6. Institute for Chemical and Physical Process, CNR, c/o Physics Dep. at Sapienza University, P-le A. Moro 5, 00185, Roma (Italy)

Description

We monitored bone regeneration in a tissue engineering approach. To visualize and understand the structural evolution, the samples have been measured by X-ray micro-diffraction. We find that bone tissue regeneration proceeds through a multi-step mechanism, each step providing a specific diffraction signal. The large amount of data have been classified according to their structure and associated to the process they came from combining Neural Networks algorithms with least square pattern analysis. In this way, we obtain spatial maps of the different components of the tissues visualizing the complex kinetic at the base of the bone regeneration

Additional details

Identifiers

Publishing Information

Journal Title
Applied Physics Letters
Journal Volume
103
Journal Issue
25
Journal Page Range
p. 253703-253703.4
ISSN
0003-6951
CODEN
APPLAB

Optional Information

Notes
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