Self-supervised image representation

Whether cells, nerves, or blood vessels, fully capturing the morphology of biological structures is a challenging task. We develop methods to represent meaningful visual features captured in images in a label-free manner. In particular in biomedical images where labeling requires often additional expertise, the possibility to explore image data in an unsupervised manner can guide further targeted analyses.

 

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