Imaging regenerating bone tissue based on neural networks applied to micro-diffraction measurements
- Institute of Crystallography, CNR, via Salaria Km 29.300, I-00015, Monterotondo Roma (Italy)
- Centro Fermi -Museo Storico della Fisica e Centro Studi e Ricerche 'Enrico Fermi', Roma (Italy)
- Deutsches Elektronen-Synchrotron DESY, Notkestraße 85, D-22607 Hamburg (Germany)
- European Synchrotron Radiation Facility, B. P. 220, F-38043 Grenoble Cedex (France)
- 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)
- Institute for Chemical and Physical Process, CNR, c/o Physics Dep. at Sapienza University, P-le A. Moro 5, 00185, Roma (Italy)
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.
- OSTI ID:
- 22217769
- Journal Information:
- Applied Physics Letters, Vol. 103, Issue 25; Other Information: (c) 2013 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA); ISSN 0003-6951
- Country of Publication:
- United States
- Language:
- English
Similar Records
Comparison of the bone regeneration ability between stem cells from human exfoliated deciduous teeth, human dental pulp stem cells and human bone marrow mesenchymal stem cells
Fast and interpretable classification of small X-ray diffraction datasets using data augmentation and deep neural networks
Convolutional Neural Network for Segmenting Micro-X-ray Computed Tomography Images of Wood Cellular Structures
Journal Article
·
Thu Mar 15 00:00:00 EDT 2018
· Biochemical and Biophysical Research Communications
·
OSTI ID:22217769
+3 more
Fast and interpretable classification of small X-ray diffraction datasets using data augmentation and deep neural networks
Journal Article
·
Fri May 17 00:00:00 EDT 2019
· npj Computational Materials
·
OSTI ID:22217769
+9 more
Convolutional Neural Network for Segmenting Micro-X-ray Computed Tomography Images of Wood Cellular Structures
Journal Article
·
Thu Jul 13 00:00:00 EDT 2023
· Applied Sciences
·
OSTI ID:22217769
+6 more