Machine learning techniques improve X-ray materials analysis
Summary
The team have demonstrated that machine learning is capable in conducting the segmentation analysis for the refraction contrast CT, which is especially useful for visualising the three-dimensional structure in samples with small density differences between regions of interest, such as epoxy resins. "Until now, no general segmentation analysis method for synchrotron radiation refraction contrast CT has been reported," says first author Satoru Hamamoto. Building on the existing machine learning model greatly reduced the amount of training data needed to get results. "Weve demonstrated that fast and accurate segmentation analysis is possible using machine learning methods, at a reasonable computational cost, and in a way that should allow non-experts to achieve levels of accuracy similar to experts," says Takaki Hatsui, who led the research group. The researchers carried out a proof-of-concept analysis in which they successfully detected regions created by water within an epoxy resin.