Deep LOGISMOS: Deep learning graph-based 3D segmentation of pancreatic tumors on CT scans

@article{Guo2018DeepLD,
  title={Deep LOGISMOS: Deep learning graph-based 3D segmentation of pancreatic tumors on CT scans},
  author={Zhihui Guo and Ling Zhang and Le Lu and Mohammadhadi Bagheri and Ronald M. Summers and Milan Sonka and Jianhua Yao},
  journal={2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)},
  year={2018},
  pages={1230-1233}
}
  • Zhihui GuoLing Zhang Jianhua Yao
  • Published 25 January 2018
  • Computer Science
  • 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)
This paper reports Deep LOGISMOS approach to 3D tumor segmentation by incorporating boundary information derived from deep contextual learning to LOGISMOS — layered optimal graph image segmentation of multiple objects and surfaces. Accurate and reliable tumor segmentation is essential to tumor growth analysis and treatment selection. A fully convolutional network (FCN), UNet, is first trained using three adjacent 2D patches centered at the tumor, providing contextual UNet segmentation and… 

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