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Tooth Instance Segmentation from Cone-Beam CT Images through Point-based Detection and Gaussian Disentanglement
The primary significance of the proposed method is two-fold: 1) the introduction of a point-based tooth detection framework that does not require additional classification and 2) the design of a novel loss function that effectively separates Gaussian distributions based on heatmap responses in the point-based detection framework.
Individual Tooth Detection and Identification from Dental Panoramic X-Ray Images via Point-wise Localization and Distance Regularization
The accuracy of identification achieved a precision of 0. 997 and recall value of 0. 972.
Pose-Aware Instance Segmentation Framework from Cone Beam CT Images for Tooth Segmentation
The primary significance of the proposed method is two-fold: 1) an introduction of pose-aware VOI realignment followed by a robust tooth detection and 2) a metal-robust CNN framework for accurate tooth segmentation.
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