Segmented mandible structures are used to effectively visualize the mandible volumes and to evaluate particular mandible properties quantitatively. In this paper, we trained a convolutional neural network (cnn) to produce automatic segmentations of the mandible and lower dentition from cbct scans A dataset of 90 cbct scans was annotated as ground truth for mandibular canal segmentation.
Samnime (@samnimetitties_) • Instagram photos and videos
The application of deep learning in developing automated segmentation models offers the potential for substantial reductions in the time required for manual segmentation.
