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Published in:
2022 | OriginalPaper | Chapter
Tibia Cortical Bone Segmentation in Micro-CT and X-ray Microscopy Data Using a Single Neural Network
Authors : Oliver Aust, Mareike Thies, DanielaWeidner, FabianWagner, Sabrina Pechmann, Leonid Mill, Darja Andreev, Ippei Miyagawa, Gerhard Krönke, Silke Christiansen, Stefan Uderhardt, Andreas Maier, Anika Grüneboom
Published in: Bildverarbeitung für die Medizin 2022
Publisher: Springer Fachmedien Wiesbaden
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X-ray microscopy (XRM) allows the investigation of osteocyte lacunae and recently discovered trans-cortical vessels in murine tibia bones due to higher resolution than conventional micro-CT (μCT) approaches. However, segmentation methods for XRM data are not yet established. Here, we propose a deep learning approach utilizing a U-Net-based neural network trained on a similar modality – μCT – that is capable of segmenting in both domains. We altered the XRM data to more closely resemble the μCT data to allow segmentation in the shifted XRM domain. Segmentation error on μCT data was evaluated by the F1 score (0.954) and IoU (0.913), whereas the segmentation on XRM data was verified visually. We conclude that the obtained model indeed allows the segmentation of cortical bone in both XRM and μCT data, although it was only trained on μCT images.