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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 337–341 of 341 filtered models
Glomerulus and nuclei detection in whole-slide pathology images, predicting a bounding circle rather than a box for rotation-consistent localization.
Self-supervised 3D pretrained models for CT and MRI that learn anatomical representations from unlabeled volumes and transfer to segmentation tasks.
Pretrained 3D-ResNet backbones for volumetric medical image analysis, co-trained across eight CT and MRI segmentation datasets for transfer learning.
3D convolutional network that predicts subcellular fluorescence labels from transmitted-light microscopy, enabling label-free imaging of living cells.
Nucleus instance segmentation for fluorescence microscopy and H&E histology, predicting a star-convex polygon per pixel to separate crowded nuclei.