Synthetic data enables human-grade microtubule analysis with foundation models for segmentation
Fig 8
Qualitative comparison on an unseen, real-world in vitro reconstituted MT assay.
For each method, we show predictions after HPO on 10 synthetic images from SynthMT (few-shot setting). The selected real image is particularly challenging, as it contains many intersecting MTs and exhibits a low signal-to-noise ratio (SNR), exposing a wide range of failure modes. For anchor-point methods such as FIESTA and TARDIS, only the first and last predicted points per instance are shown for visual clarity. Underneath each image we report the mean SKIoU value for this specific image, in order to correlate it with a visual impression. SAM3Text clearly performs best in this setting, while all other methods show limitations that may hinder their suitability for large-scale fully automated analysis. For more comparisons and dynamic exploration of this kind, we refer to our project page at DATEXIS.github.io/SynthMT-project-page.