Machine learning dental segmentation methods using sparse voxel representations

Machine learning dental segmentation methods using sparse voxel representations

Methods for automatically segmenting a 3D model of a patient's teeth may include scanning a patient's dentition and converting the scan data into a 3D model, including a sparse voxel representation of the 3D model. Features can be extracted from the sparse voxel representation of the 3D mo...

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Bibliographische Detailangaben
Hauptverfasser: Gudchenko, Roman, Potapenko, Ivan, Baskanov, Anton, Guskov, Dmitry, Cramer, Christopher E, Zhirnov, Nikolay, Ulianenko, Elizaveta, Solovyev, Roman, Paraketsov, Vasily, Toporkov, Mikhail, Grebenkin, Sergey, Durdin, Denis, Ischeykin, Dmitrii, Gorodilov, Mikhail, Karsakov, Aleksandr Sergeevich, Vovchenko, Alexander, Anikin, Aleksandr
Format: Patent
Sprache:eng
Schlagworte:
APPARATUS OR METHODS FOR ORAL OR DENTAL HYGIENE
CALCULATING
COMPUTING
COUNTING
DENTISTRY
HUMAN NECESSITIES
HYGIENE
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
MEDICAL OR VETERINARY SCIENCE
PHYSICS
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Beschreibung
Zusammenfassung:Methods for automatically segmenting a 3D model of a patient's teeth may include scanning a patient's dentition and converting the scan data into a 3D model, including a sparse voxel representation of the 3D model. Features can be extracted from the sparse voxel representation of the 3D model and input into a machine learning model to train the machine learning model to segment the 3D model into individual dental components.