Robust Cell Segmentation for Size Distribution Estimation via Synthetic‐Data Training

Polyhydroxyalkanoates (PHAs) are biodegradable and biocompatible plastics, yet large-scale production remains limited by costly batch operations and the lack of online analytical tools. Monitoring cell size distribution serves as a strong surrogate for intracellular PHA content, but training robust cell segmentation models for industrial bioprocesses requires extensive manual annotation, which is highly labor-intensive and impractical for densely populated microscopy images. To address this critical bottleneck, an annotation-free cell segmentation and size estimation pipeline tailored for real time monitoring is presented. Rather than relying on architectural modifications, this framework introduces a system-level automated training strategy: individual cells are automatically extracted from diluted-sample microscopy images using edge enhancement and rule-based binarization, then augment…