Cell-DINO: Self-supervised image-based embeddings for cell fluorescent microscopy
Fig 4
Performance evaluation of Cell-DINO on the HPA dataset.
All reported results are the F1-scores of the corresponding classification task. There are two classification tasks: protein localization (PL/green shades) and cell-line (CL/blue shades) prediction. Each task is evaluated in two versions of the HPA dataset: field-of-view (dark colors) images and single-cell images (light colors). See legend in the bottom-right. Results are presented in a grid of bar-plots colored according to the task and dataset, and organized by pretraining data (columns) and model initialization (rows). Pre-training data goes from no supervision with any labels (left column), to medium supervision with cell line labels (center column), and strong supervision with protein localization labels (right column). The rows consider random initialization (top row), pre-trained DINOv2 models without self-supervision with cell images (center row), and initialization with DINOv2 pre-trained weights with additional self-supervision with cellular images (bottom row). The average score in the top-right corner of the figure identifies each method with a colored icon according to the ranking from best to worst performance. The results of Cell-DINO fine-tuned are reported in Table C in S1 Text.