Martin Abt

This paper introduces DeepCell Types, a language-informed vision model for spatial proteomics cell phenotyping that generalizes across diverse datasets and marker panels.

Bounding boxes from a transformer detector let the Segment Anything Model segment cells automatically; one generalist model beats generalist Cellpose and matches inter-annotator agreement across mammalian, yeast and bacterial images.