Segmentation of nanotomographic cortical bone images for quantitative characterization of the osteoctyte lacuno-canalicular network
- Synchrotron Soleil, L’Orme des Merisiers, 91192 Saint-Aubin (France)
- Paul Scherrer Institut, 5232 Villigen PSI (Switzerland)
- Univ Orléans, I3MTO, Ea 4708, 45000 Orléans (France)
A newly developed data processing method able to characterize the osteocytes lacuno-canalicular network (LCN) is presented. Osteocytes are the most abundant cells in the bone, living in spaces called lacunae embedded inside the bone matrix and connected to each other with an extensive network of canals that allows for the exchange of nutrients and for mechanotransduction functions. The geometrical three-dimensional (3D) architecture is increasingly thought to be related to the macroscopic strength or failure of the bone and it is becoming the focus for investigating widely spread diseases such as osteoporosis. To obtain 3D LCN images non-destructively has been out of reach until recently, since tens-of-nanometers scale resolution is required. Ptychographic tomography was validated for bone imaging in [1], showing clearly the LCN. The method presented here was applied to 3D ptychographic tomographic images in order to extract morphological and geometrical parameters of the lacuno-canalicular structures.
- OSTI ID:
- 22494402
- Journal Information:
- AIP Conference Proceedings, Vol. 1696, Issue 1; Conference: XRM 2014: 12. international conference on X-ray microscopy, Melbourne (Australia), 26-31 Oct 2014; Other Information: (c) 2016 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA); ISSN 0094-243X
- Country of Publication:
- United States
- Language:
- English
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