Segmentation of nanotomographic cortical bone images for quantitative characterization of the osteoctyte lacuno-canalicular network

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 can...

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Bibliographic Details
Main Authors: Ciani, A., Guizar-Sicairos, M., Diaz, A., Holler, M., Pallu, S., Achiou, Z., Jennane, R., Toumi, H., Lespessailles, E., Kewish, C. M.
Format: Conference Proceeding
Language:English
Subjects:
Biocompatibility
BIOMEDICAL RADIOGRAPHY
BONE CELLS
Canals
CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS
DATA PROCESSING
FAILURES
Image segmentation
INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY
Medical imaging
Nutrients
OSTEOPOROSIS
RESOLUTION
SKELETON
THREE-DIMENSIONAL CALCULATIONS
TOMOGRAPHY
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Summary: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.
ISSN:0094-243X
1551-7616
DOI:10.1063/1.4937534