DeepCenterline: a Multi-task Fully Convolutional Network for Centerline Extraction

@inproceedings{Guo2019DeepCenterlineAM,
  title={DeepCenterline: a Multi-task Fully Convolutional Network for Centerline Extraction},
  author={Zhihui Guo and Junjie Bai and Yi Lu and Xin Wang and Kunlin Cao and Qi Song and Milan Sonka and Youbing Yin},
  booktitle={IPMI},
  year={2019}
}
A novel centerline extraction framework is reported which combines an end-to-end trainable multi-task fully convolutional network (FCN) with a minimal path extractor. [] Key Method The method generates single-pixel-wide centerlines with no spurious branches. It handles arbitrary tree-structured object with no prior assumption regarding depth of the tree or its bifurcation pattern. It is also robust to substantial scale changes across different parts of the target object and minor imperfections of the object…

Learning tree-structured representation for 3D coronary artery segmentation

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