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Canal-Net for automatic and robust 3D segmentation of mandibular canals in CBCT images using a continuity-aware contextual network

Canal-Net for automatic and robust 3D segmentation of mandibular canals in CBCT images using a continuity-aware contextual network

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A deep learning-based automatic segmentation of zygomatic bones from cone-beam computed tomography images: A proof of concept - ScienceDirect

BIR Publications

Comparison of 2D, 2.5D, and 3D segmentation networks for maxillary sinuses and lesions in CBCT images, BMC Oral Health

SinusC-Net for automatic classification of surgical plans for maxillary sinus augmentation using a 3D distance-guided network

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Automatic classification of 3D positional relationship between mandibular third molar and inferior alveolar canal using a distance-aware network, BMC Oral Health

Automatic classification of 3D positional relationship between mandibular third molar and inferior alveolar canal using a distance-aware network, BMC Oral Health

PDF] Automated tracking of the mandibular canal in CBCT images using matching and multiple hypotheses methods

PDF] Segmentation of the mandibular canal in cone-beam CT data

PDF) Automatic classification of 3D positional relationship between mandibular third molar and inferior alveolar canal using a distance-aware network

QCBCT-NET for direct measurement of bone mineral density from quantitative cone-beam CT: a human skull phantom study. - Abstract - Europe PMC

Automatic classification of 3D positional relationship between mandibular third molar and inferior alveolar canal using a distance-aware network, BMC Oral Health