{"id":22631942,"url":"https://github.com/alleninstitute/deep-neurographs","last_synced_at":"2025-04-11T20:10:31.074Z","repository":{"id":181328237,"uuid":"659400602","full_name":"AllenInstitute/deep-neurographs","owner":"AllenInstitute","description":"A Python package that corrects split mistakes in a fragmented neuron segmentation using a graph neural 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GraphTrace\n\n[![License](https://img.shields.io/badge/license-MIT-brightgreen)](LICENSE)\n![Code Style](https://img.shields.io/badge/code%20style-black-black)\n[![semantic-release: angular](https://img.shields.io/badge/semantic--release-angular-e10079?logo=semantic-release)](https://github.com/semantic-release/semantic-release)\n![Interrogate](https://img.shields.io/badge/interrogate-37.5%25-red)\n![Coverage](https://img.shields.io/badge/coverage-100%25-brightgreen?logo=codecov)\n![Python](https://img.shields.io/badge/python-\u003e=3.7-blue?logo=python)\n\n\u003cb class=\"red-text\"\u003e Note: This page is under development \u003c/b\u003e\n\u003cbr\u003e\n\nGraphTrace is a Python library that automatically corrects splits in fragmented neuron segmentations from whole-brain images.\n\n\u003cp\u003e\n  \u003cimg src=\"imgs/result.png\" width=\"900\" alt=\"\"\u003e\n  \u003cbr\u003e\n   \u003cb\u003e Figure: \u003c/b\u003eNeuron fragments corrected by using GraphTrace.\n\u003c/p\u003e\n\nBriefly describe inference pipeline, to do...\n\n- Graph Construction: Reads neuron fragments stored as swc files and loads them into a Networkx graph.\n- Proposals: Generates potential connections between nearby fragments to correct false splits in the segmentation\n- Feature Generation: Extracts geometric and image-based features from the graph to be utilized by a machine learning model that classifies the proposals.\n- Graph Neural Network (GNN) Inference: Predicts whether to accept or reject proposals based on the generated features and graphical structure.\n- Graph Update: Integrates inference results by merging fragments corresponding to an accepted proposal.\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"imgs/pipeline.png\" width=\"800\" alt=\"pipeline\"\u003e\n    \u003cbr\u003e\n  \u003cb\u003e Figure: \u003c/b\u003eVisualization of split correction pipeline, see Inference section for description of each step.\n\u003c/p\u003e\n\n## Usage\n\nTo do...\n\n## Inference\n\n### Step 1: Graph Construction\n\nTo do...\n\n### Step 2: Proposal Generation\n\nTo do...\n\n### Step 3: Proposal Classification\n\nTo do...\n\n## Installation\nTo use the software, in the root directory, run\n```bash\npip install -e .\n```\n\n## Contact Information\nFor any inquiries, feedback, or contributions, please do not hesitate to contact us. You can reach us via email at anna.grim@alleninstitute.org or connect on [LinkedIn](https://www.linkedin.com/in/anna-m-grim/).\n\n## License\nGraphTrace is licensed under the MIT License.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falleninstitute%2Fdeep-neurographs","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falleninstitute%2Fdeep-neurographs","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falleninstitute%2Fdeep-neurographs/lists"}