All Competitors
Every biological foundation model, evaluated and ranked by the bio.rodeo team
Applications
Architectures
Learning Paradigms
Biological Subjects
Showing 1–12 of 12 filtered models
Cellpose-SAM
HHMI Janelia Research Campus
Generalist cell segmentation model combining SAM's ViT-L backbone with Cellpose flow fields. First model to surpass average human annotators on the Cellpose benchmark.
OmniEM
Peking University
Unified electron microscopy image analysis toolkit built on EM-DINO, a vision foundation model pretrained on 5 million diverse EM images.
Cellpose 3
HHMI Janelia Research Campus
Generalist cell segmentation framework with a super-generalist cyto3 model and one-click image restoration networks optimized for downstream segmentation quality.
BiomedParse
Microsoft Research
A biomedical foundation model for joint segmentation, detection, and recognition across nine imaging modalities using natural language prompts.
CryoSAM
Xu Lab
Training-free cryo-ET tomogram segmentation that adapts SAM and DINOv2 for 3D volumetric data, enabling full tomogram segmentation from a single user prompt.
CryoViT
Stanford University
Semi-supervised cryo-ET segmentation framework that adapts DINOv2 vision transformers for 3D organelle annotation using sparse 2D slice labels.
Cytoland
Chan Zuckerberg Biohub / Mehta Lab
A suite of virtual staining models that translate label-free microscopy images into fluorescent-equivalent staining of nuclei and plasma membranes.
CellSeg3D
Mathis Lab
Self-supervised 3D cell segmentation for fluorescence microscopy using WNet3D and Swin-UNetR, achieving supervised-level performance without annotated training data.
CellSAM
Van Valen Lab
Universal cell segmentation model adapting Meta's SAM for biology. Segments mammalian cells, yeast, and bacteria across diverse imaging modalities with human-level accuracy.
CellViT
Institute for AI in Medicine
Vision Transformer for cell instance segmentation and classification in H&E digital pathology, extended by CellViT++ with foundation model backbones and few-shot adaptation.
Cellpose 2.0
HHMI Janelia Research Campus
Human-in-the-loop cell segmentation framework enabling custom model training from as few as 100-200 corrected annotations.
Cellpose
HHMI Janelia Research Campus
Generalist deep learning algorithm for cell and nucleus instance segmentation using simulated diffusion flows, without per-dataset retraining.