βοΈ New in #eLife: #CellSeg3D introduces #WNet3D, a self-supervised 3D #segmentation method for #microscopy data β no labels needed. Claims to outperform #Cellpose/#StarDist on 4 datasets. Includes #opensource plugin (#Napari) + full 3D annotated #cortex dataset. Will test it later.
π https://elifesciences.org/articles/99848
#DeepLearning #Neuroscience
CellSeg3D, Self-supervised 3D cell segmentation for fluorescence microscopy
Self-supervised deep learning models can accurately perform 3D segmentation of cell nuclei in complex biological tissues, enabling scalable analysis in settings with limited or no ground truth annotations.
Fabrizio Musacchio