Pipeline: (3D) Single-Cell_Adherent

This pipeline segments and analyzes individual adherent cells in 3D holotomographic images using a rule-based algorithm. It is optimized for low-confluency samples where cells are well-separated and spread thinly on the substrate. The algorithm is well-suited for distinguishing single cells with thin cytoplasm and low refractive index, enabling accurate per-cell segmentation.

By leveraging refractive index-based detection, the pipeline provides both per-cell and total measurements, making it ideal for studying growth dynamics, morphological variation, and cellular responses to external stimuli.

Output: Segmented 3D cell masks, Labeled individual cells, Per-cell and total measurements



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