ALT valuation of different methods for pixel classification (top) and object classification (bottom) on the LIVECell dataset. Dark green bars show the F1-Score, which measures the classification / segmentation quality (higher is better), light green bars show the runtimes. Five different settings are compared for each task: Ilastik features + random forest (RF), microSAM embeddings + RF, SAM2 embeddings + RF, and uSAM, SAM2 + attentive probing (DeAP and ObAP). microSAM feature perform best for RF based methods, attentive probing outperforms RF based approaches, but at a much higher runtime.

ALT A cochlea imaged in light-sheet microscopy (right) with staining for spiral ganglion neurons (red) and inner hair cells (blue). You will develop AI-based methods to analyze these structures, for example via segmentation of the individual cells (right) that will support gene therapy development for hearing loss and a better overall understanding of the anatomy of hearing.