from ultralytics import YOLO
from huggingface_hub import hf_hub_download

# Download and load model
model_path = hf_hub_download(
    repo_id="Center-for-Computational-Neuropathology/Lewy_body",
    filename="best.pt"
)
model = YOLO(model_path)

# Run inference
results = model.predict("synuclein_stained_image.jpg", conf=0.25, imgsz=640)

Clinical Relevance

Detects Lewy bodies in:

Parkinson's Disease (PD)
Dementia with Lewy Bodies (DLB)
Parkinson's Disease Dementia (PDD)

Key Features

✅ Best overall performance among four pathology types
✅ Stable training convergence
✅ Balanced precision-recall trade-off
✅ Eliminates inter-observer variability

Limitations

Requires α-synuclein immunohistochemistry staining
Performance varies with staining protocols
May not distinguish Lewy bodies from Lewy neurites
Requires expert validation for clinical use

Citation

bibtex

@article{neuropath_yolo_2025,
  title={Automated Detection of Neurodegenerative Pathology Using YOLOv11},
  author={[Authors]},
  journal={[Journal]},
  year={2025}
}