Modelpublic

Noel-Niko/dinov2-upernet-20260322-histology-annotation-mouse

sourceHugging Faceapache-2.0updated 6mo agoView on Hugging Face

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Model Card

Brain Region Segmentation — Mouse Brain

DINOv2-Large + UperNet model fine-tuned for semantic segmentation of mouse brain structures in Nissl-stained histological sections.

Model Details

Attribute	Value
Architecture	DINOv2-Large (304M) + UperNet (38M)
Classes	1,328
Input Size	518x518
Training Data	Allen Brain Institute CCFv3 10um Nissl staining
mIoU (center-crop)	74.8%
mIoU (sliding window)	79.1%

Usage

bash

git clone https://github.com/Noel-Niko/histological-image-analysis
cd histological-image-analysis
make install
make download-models-mouse
make annotate-mouse IMAGES=/path/to/your/slides/

Paper

Transfer Learning for Ultra-Fine-Grained Brain Region Segmentation: An Ablation Study with DINOv2 + UperNet on 1,328 Allen Mouse Brain Atlas Structures

We conduct a systematic ablation study across 9 training runs on pixel-level segmentation of 1,328 brain structures from the Allen Mouse Brain Atlas CCFv3. The two most impactful interventions are backbone partial fine-tuning (+8.5% mIoU) and extended training from 100 to 200 epochs (+6.0% mIoU). Three attempted improvements — weighted Dice+CE loss, aggressive augmentation, and test-time augmentation — all degrade performance.

See `paper.md` in this repo for the full paper.

Citation

If you use this model, please cite the training data sources and the paper included in this repository.

Repository

Full source code, training notebooks, and all models: https://github.com/Noel-Niko/histological-image-analysis

Maintaining This Repo

To update model weights, papers, or this README:

bash

cd histological-image-analysis
export HUGGING_FACE_TOKEN=hf_your_token_here

# Update model weights (Databricks or local):
jupyter notebook notebooks/upload_models_to_hf.ipynb

# Update papers + READMEs (local only):
jupyter notebook notebooks/upload_papers_to_hf.ipynb