Accurate segmentation of individual particles is critical for the analysis. In Case Study 1, segmentation errors were less problematic because particle labels were not required to match between pristine and cycled states. However, in Case Study 2, maintaining consistent particle labels across different SoC was essential. This was addressed using a seed-based segmentation approach, and by removing inconsistent labels from the dataset with dataframe merging. The segmentation of smaller particles posed particular challenges due to phase contrast enhancement, and merged or erroneous labels. To mitigate this, the smallest quartile of particles was excluded from most quantitative analysis.