TY - GEN
T1 - Predictive Treatment of Third Molars Using Panoramic Radiographs and Machine Learning
AU - Aravena, Hector
AU - Arredondo, Miguel
AU - Fuentes, Carlos
AU - Taramasco, Carla
AU - Alcocer, Diego
AU - Gatica, Gustavo
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Panoramic radiography is a routine technology used to diagnose oral and maxillofacial pathology; it has the advantages of low cost, high speed, and safety because of the reduced dose and exposure time to radiation. Third molars are responsible for benign or malignant tumors that can result in neurological problems, diminish the resistance to fractures owing to their position in the bone and frequently generate infectious problems. The appropriate planning and classification allow patients to be treated safely and help reduce waiting lists. We used panoramic radiography and machine learning to identify the inclination, depth, and available space of third molars to support diagnosis and surgical treatment. In experiments, our approach identified third molars with 100% accuracy The molars were classified as per the Winter and Pell-Gregory classification schemes having high accuracies of >80%. The contribution of this work adds value to the imaging diagnosis, allowing an estimation of the disinclusion time of third molars to support the surgical management of the operating room.
AB - Panoramic radiography is a routine technology used to diagnose oral and maxillofacial pathology; it has the advantages of low cost, high speed, and safety because of the reduced dose and exposure time to radiation. Third molars are responsible for benign or malignant tumors that can result in neurological problems, diminish the resistance to fractures owing to their position in the bone and frequently generate infectious problems. The appropriate planning and classification allow patients to be treated safely and help reduce waiting lists. We used panoramic radiography and machine learning to identify the inclination, depth, and available space of third molars to support diagnosis and surgical treatment. In experiments, our approach identified third molars with 100% accuracy The molars were classified as per the Winter and Pell-Gregory classification schemes having high accuracies of >80%. The contribution of this work adds value to the imaging diagnosis, allowing an estimation of the disinclusion time of third molars to support the surgical management of the operating room.
KW - artificial intelligence
KW - technology in dentistry
KW - third molar prediction
UR - http://www.scopus.com/inward/record.url?scp=85167589708&partnerID=8YFLogxK
U2 - 10.1109/WiMob58348.2023.10187860
DO - 10.1109/WiMob58348.2023.10187860
M3 - Conference contribution
AN - SCOPUS:85167589708
T3 - International Conference on Wireless and Mobile Computing, Networking and Communications
SP - 123
EP - 128
BT - 2023 19th International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2023
PB - IEEE Computer Society
T2 - 19th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2023
Y2 - 21 June 2023 through 23 June 2023
ER -