Canal-net for automatic and robust 3d segmentation of mandibular canals in cbct images using a continuity-aware contextual network

HIGHLIGHTS

• who: Bo-Soung Jeoun from the National University have published the paper: Canal-Net for automatic and robust 3D segmentation of mandibular canals in CBCT images using a continuity-aware contextual network, in the Journal: Scientific Reports Scientific Reports
• what: The authors proposed a continuity-aware contextual network (Canal-Net) which learned 3D local anatomical contextual information and the global continuity of the MC complementally to segment the MC with high consistent accuracy throughout the entire MC volume in cone-beam CT (CBCT) images.
• how: The patient data were obtained at 80 kVp . . .
  

   

  

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