library_name: timm
license: mit
pipeline_tag: image-feature-extraction
inference: false
tags:
- microscopy
- single-cell
- self-supervised
- dinov2
- vision-transformer
- biology
scdino-v2-base
Self-supervised Vision Transformer (DINOv2) for 5-channel single-cell microscopy crops of human peripheral blood mononuclear cells (PBMCs). It returns one 128-dimensional embedding per crop.
Input: 50×50 px crops with 5 channels (H, W, C), in this order:
# Channel Markers 1 647 nm CD3 (APC), CD14 (Alexa Fluor 647) 2 Brightfield – 3 DAPI – 4 488 nm CD4, CD19 (FITC) 5 594 nm CD8, CD16, CD56 (PE), CD20 (Alexa Fluor 594) Data: A labelled set of more than 1.3 million single-cell images of seven immune cell types is openly available: Morphologically annotated single-cell images of human PBMCs.
Usage
See the README of the code repository, https://github.com/JonasMeirer/scDINOv2, for how to load the model, preprocess crops and evaluate embeddings.
Usage on images from other microscopes, stains, cells or crop sizes might need new normalization statistics and retraining.
Not a diagnostic tool, and not for clinical use.
Citation
The publication describing this model is currently under review. This section will be updated with the reference once it is published.
License
MIT, like the scDINO code. Training used timm (Apache-2.0) and code vendored from Lightly (MIT).