Computational Dentistry with 3d Point Cloud Segmentation
( go to the article → https://datafloq.com/read/computational-dentistry-3d-point-cloud-segmentation/18311 )
Modern dentistry has undergone noteworthy changes owing to the technical advancements in the field of machine learning-backed AI models. Upgraded imaging methods have now been incorporated in dentistry to ensure heightened efficiency levels and providing a reliable experience to customers. Significant improvements can be seen with treatment planning and diagnostic changes using computation dentistry that encompasses intra-oral and extra-oral optical imaging; herein, the use of data is also evidential for the machine learning-backed AI models enabled with point cloud labeling dataThe intra-oral scanners imaging devices use light for capturing the surface of the anatomical structure of a patient’s mouth and the project pattern of the mouth is measured by imaging sensors; creating an accurate 3D point cloud. Obtained 3D point cloud shows the geometrical profile of tooth and gingiva in high spatial resolution (30-80 points per mm2) and equally high spatial accuracy. For AI implementation, this 3D point cloud data is further used for orthodontic planning and treatment planning in modern dentistry. This also enables providing a detailed view of the anatomical structure of the clinical dental application.AI and Deep neural networks in modern dentistry The same methodologies have been used so far for the segmentation of individual teeth ...Read More on Datafloq
Oct. 1, 2021, 9:05 a.m.
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