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Synthetic data enables human-grade microtubule analysis with foundation models for segmentation

Fig 4

Real IRM images with human ground-truth labels (for evaluation only).

Four exemplary frames from the 66 video crops of size used to establish target distributions (each containing 10 randomly sampled frames). Each image shows individual in vitro MTs growing from stabilized seeds under different experimental conditions, exhibiting natural variation in quantity, length, curvature, overlapping MTs, contrast, noise characteristics, filament density, and background properties. These target distributions act as references in the optimization process (Fig 3), where DINOv2 embeddings of guide the synthetic data generation. Ground-truth labels from one annotator are overlaid to illustrate the filament structures present in the real data; they are used solely for later method evaluation and are not required for generating the synthetic dataset SynthMT.

doi: https://doi.org/10.1371/journal.pcbi.1013901.g004