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Found 4 papers, 0 papers with code
Automatic 3D Registration of Dental CBCT and Face Scan Data using 2D Projection Images
A main contribution of this study is that the proposed method does not require annotated training data of facial landmarks because it uses a pre-trained facial landmark detection algorithm that is known to be robust and generalized to various 2D face image models.
Fully automatic integration of dental CBCT images and full-arch intraoral impressions with stitching error correction via individual tooth segmentation and identification
The proposed method is intended not only to compensate the low-quality of CBCT-derived tooth surfaces with IOS, but also to correct the cumulative stitching errors of IOS across the entire dental arch.
Automated 3D cephalometric landmark identification using computerized tomography
This paper presents a semi-supervised DL method for 3D landmarking that takes advantage of anonymized landmark dataset with paired CT data being removed.
Automatic Three-Dimensional Cephalometric Annotation System Using Three-Dimensional Convolutional Neural Networks
The purpose of this study was to evaluate the accuracy of our newly-developed system using a deep learning algorithm for automatic 3D cephalometric annotation.
