/DeepBranchTracer

DeepBranchTracer: A Generally-Applicable Approach to Curvilinear Structure Reconstruction Using Multi-Feature Learning

Primary LanguagePython

DeepBranchTracer: A Generally-Applicable Approach to Curvilinear Structure Reconstruction Using Multi-Feature Learning

DeepBranchTracer is a novel method for reconstructing curvilinear structures from 2D and 3D images. It leverages deep learning to extract both image and geometric features, enabling accurate and continuous reconstruction of line-like objects, such as roads, vessels, and neurons.

Usage

It is recommended to use neutube software to visualize images and SWC files. neutube can be downloaded from https://neutracing.com/.

Citation

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@inproceedings{liu2024deepbranchtracer,
  title={DeepBranchTracer: A Generally-Applicable Approach to Curvilinear Structure Reconstruction Using Multi-Feature Learning},
  author={Liu, Chao and Zhao, Ting and Zheng, Nenggan},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={38},
  number={4},
  pages={3548--3557},
  year={2024}
}