Automated Detection of Missing Tooth Regions in CBCT Slices for Dental Implant Planning using CNN with Transfer Learning

Naufal, Mohammad Farid and Fatichah, Chastine and Astuti, Eha Renwi and Putra, Ramadhan Hardani and Prambudi, Katarina Inezita (2025) Automated Detection of Missing Tooth Regions in CBCT Slices for Dental Implant Planning using CNN with Transfer Learning. In: TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON), 1-4 December 2024, Singapore.

PDF Automated_Detection_of_Missing_Tooth_Regions_in_CBCT_Slices_for_Dental_Implant_Planning_Using_CNN_with_Transfer_Learning.pdf - Published Version Download (875kB)

Abstract

Detecting the missing tooth region in Cone Beam Computed Tomography (CBCT) slices is crucial for dentists when planning dental implant placement. It allows dentists to accurately identify regions where tooth is missing and assess the suitability of these regions for dental implant placement. However, manually detecting CBCT slices to determine these areas can be time-consuming for dentists. Previous studies have primarily focused on panoramic radiographs or 3D CBCT volumes to detect missing tooth, but none have classified missing tooth in CBCT slices that follow the jaw curve, which is crucial for dental implant planning. This study proposes a new approach that leverages CNN with transfer learning using wellknown architectures: InceptionV3, VGG16, MobileNetV2, ResNet50, and ResNet101 to detect missing tooth regions for dental implant placement in Cone Beam Computed Tomography (CBCT) slices that follow the jaw curve. Additionally, histogram equalization enhances the CBCT slices before the classification process. K-fold cross-validation with k=5 is employed to evaluate the performance of the proposed method. The results indicate that the ResNet101 architecture achieves the highest average F1 score of 98.2%. Automated detection of missing tooth regions can significantly reduce the time and effort required to plan dental implants, allowing dentists to focus more on patient care.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	missing tooth, detection, CBCT, transfer learning
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Faculty of Engineering > Department of Informatic
Depositing User:	MOHAMMAD FARID NAUFAL
Date Deposited:	10 Mar 2025 02:56
Last Modified:	10 Mar 2025 02:56
URI:	http://repository.ubaya.ac.id/id/eprint/48159

Actions (login required)

View Item