Deep learning to overcome Zernike phase-contrast nanoCT artifacts for automated micro-nano porosity segmentation in bone

Deep learning to overcome Zernike phase-contrast nanoCT artifacts for automated micro-nano porosity segmentation in bone

Bone material contains a hierarchical network of micro- and nano-cavities and channels, known as the lacuna-canalicular network (LCN), that is thought to play an important role in mechanobiology and turnover. The LCN comprises micrometer-sized lacunae, voids that house osteocytes, and submicrometer-...

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Bibliographic Details
Main Authors: Andreia Silveira, Imke Greving, Elena Longo, Mario Scheel, Timm Weitkamp, Claudia Fleck, Ron Shahar, Paul Zaslansky
Format: Article
Language:English
Published: International Union of Crystallography 2024-01-01
Series:Journal of Synchrotron Radiation
Subjects:
zernike phase contrast
x-ray nanotomography
deep learning
computer-aided image segmentation
lacuna-canalicular network
sensor3d model
u-net model
Online Access:http://scripts.iucr.org/cgi-bin/paper?S1600577523009852

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http://scripts.iucr.org/cgi-bin/paper?S1600577523009852

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