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Adaptive filtering for enhancement of the osteocyte cell network in 3D microtomography images
Authors:A. Pacureanu  A. Larrue  M. Langer  C. Olivier  C. Muller  M.-H. Lafage-Proust  F. Peyrin
Affiliation:1. Centre for image analysis & Science for Life Laboratory, Uppsala University, Sweden;2. CREATIS, CNRS UMR 5220, INSERM U1044, Université de Lyon, Université Lyon 1, INSA-Lyon, Lyon, France;3. European Synchrotron Radiation Facility (ESRF), Grenoble, France;4. Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom;5. INSERM U1059, LBTO, Université Jean-Monnet, Saint-Étienne, France
Abstract:The osteocyte cell network in bone tissue is thought to orchestrate tissue adaptation and remodeling, thus holding responsibility for tissue quality. Previously, this structure has been studied mainly in 2D and its architecture and functions are not fully elucidated. The assessment of the osteocyte system is prerequisite for deeper understanding of bone remodeling and for advances in management of bone diseases. Our goal is to enable 3D isotropic imaging of bone at cellular level and to develop algorithms for quantitative image analysis of the cell network. We recently demonstrated accurate 3D imaging of this cell structure with synchrotron radiation tomography at submicrometric scale. Due to the limited spatial resolution of the imaging system and the constraints in terms of radiation dose, the images suffer from low signal to noise ratio and the detection of the cell dendrites is challenging. Here we detail a method for enhancement of the osteocyte network in human bone from 3D microtomography images. The approach combines Hessian-based 3D line enhancement and bilateral filtering. Our method enables extraction of the interconnected cells from noisy images, preserving the integrity of the cells and of their slender dendrites. Qualitative and quantitative results are presented.
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