Speaker
Description
As part of our correlative characterisation studies of biodegradable metal bone implants we have performed both synchrotron-radiation microtomography (SR-µCT) and histology sequentially on the same samples and regions of interest. Histological staining is still the gold standard for tissue visualisation yet requires multiple time-consuming sample preparation steps (fixing, embedding, sectioning and staining) before imaging is performed on individual slices, in contrast to the non-invasive and 3D nature of x-ray tomography. In the process of correlating the corresponding data sets, we are able to combine advantages of both modalities by training machine learning networks for modality transfer on SR-µCT/histology pairs to generate artificially stained 3D virtual histology data from SR-µCT datasets, with promising preliminary results.
