• Corpus ID: 248863449

Detecting micro fractures: A comprehensive comparison of conventional and machine-learning based segmentation methods

@inproceedings{Lee2021DetectingMF,
  title={Detecting micro fractures: A comprehensive comparison of conventional and machine-learning based segmentation methods},
  author={Dongwon Lee and Nikolaos K. Karadimitriou and Matthias Ruf and Holger Steeb},
  year={2021}
}
. Studying porous rocks with X-Ray Computed Tomography (XRCT) has been established as a standard procedure for the non-destructive characterization of flow and transport in porous media. Despite the recent advances in the field of XRCT, various challenges still remain due to the inherent noise and imaging artefacts in the produced data. These issues become even more profound when the objective is the identification of fractures, and/or fracture networks. One challenge is the limited contrast… 

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