Object Detection Pipeline for Nigral Neurons

Installation

Clone the Countnigra GitHub repository:

git clone https://github.com/onnonuro/countnigra.git

Tutorial with Google Colab

Google Colab is the easiest way to try this software with GPU support, especially for clinicians and pathologists who are unfamiliar with programming or do not have a local Python environment.

To get started:

1. Download tutorial.ipynb: Download tutorial.ipynb.

2. Upload tutorial.ipynb to your Google Drive: Upload the file to your Google Drive.

3. Open tutorial.ipynb with Google Colab: Sign in Google Colab and open tutorial.ipynb with it.

4. Run countnigra: Follow the instructions in the Jupyter Notebook tutorial.

   *You need a Google account and sign in to Google Colab.

Dependencies

This software was tested in the following Google Colab environment on June 6, 2026.

Python (3.12.12), torch (2.9.1), torchvision (0.24.1), ultralytics (8.0.99), numpy, pandas, seaborn, matplotlib, Pillow, opencv-python, openslide-bin, tqdm, gdown

Citation

If you use this software in your research, please cite:

Ono D, Sekiya H, Maier AR, Murray ME, Koga S, Dickson DW. Parkinsonism in Alzheimer's disease without Lewy bodies in association with nigral neuron loss: A data-driven clinicopathologic study. Alzheimers Dement. 2025 Mar;21(3):e14628. https://alz-journals.onlinelibrary.wiley.com/doi/10.1002/alz.14628