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Deep-Neurographs is a Python module that utilizes machine learning to detect and correct false splits in a predicted neuron segmentation.

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GraphTrace

License Code Style semantic-release: angular Interrogate Coverage Python

GraphTrace is a Python library that utilizes machine learning to perform automated reconstruction of a fragmented neuron segmentation from whole brain images. For a demo, we provide a Jupyter notebook that loads fragments from a predicted segmentation and automatically merges them by running GraphTrace. You can use our github code to train a deep learning model and test with a ground-truth.

Example of before and after run obtained with GraphTrace

Key Features

  • Graph Construction: Reads neuron fragments stored as swc files and loads them into a Networkx graph
  • Proposals: Generates potential connections between nearby fragments to correct false splits in the segmentation
  • Feature Generation: Extracts geometric and image-based features from the graph to be utilized by a machine learning model that classifies the proposals.
  • Graph Neural Network (GNN) Inference: Predicts whether to accept or reject proposals based on the generated features and graphical structure.
  • Graph Update: Integrates inference results by merging fragments corresponding to an accepted proposal.

Installation

To use the software, in the root directory, run

pip install -e .

To develop the code, run

git clone 
pip install -e .[dev]

Contributing

We welcome contributions from the community! If you have suggestions, improvements, or bug reports, please open an issue or submit a pull request.

License

GraphTrace is licensed under the MIT License.

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Deep-Neurographs is a Python module that utilizes machine learning to detect and correct false splits in a predicted neuron segmentation.

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