Widiasri, Monica and Arifin, Agus Zainal and Suciati, Nanik and Fatichah, Chastine and Astuti, Eha Renwi and Indraswari, Rarasmaya and Putra, Ramadhan Hardani and Za'in, Choiru (2022) Dental-YOLO: Alveolar Bone and Mandibular Canal Detection on Cone Beam Computed Tomography Images for Dental Implant Planning. IEEE Access, 10. pp. 101483-101494. ISSN 2169-3536
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Abstract
In planning a mandibular posterior dental implant, identifying the exact location of the alveolar bone (AB) and mandibular canal (MC) is essential to determine the height and width of the available bone. Cone beam computed tomography (CBCT) is a 3D imaging modality widely used for dental implant planning, which requires a lower radiation dose compared to medical CT and can provide crosssectional image quality to visualize AB and MC. The radiologist carried out the AB and MC detection processes manually on each section of the CBCT image until the appropriate area was determined for bone measurement. This process is time consuming, and the measurement accuracy depends on the ability and experience of the radiologist. This study proposes an automatic and simultaneous detection system for AB and MC based on 2D grayscale CBCT images, that can simplify and expedite dental implant planning. We introduce Dental-YOLO, an efficient version of YOLOv4 specifically developed to detect AB and MC, with two-scale feature maps at low and high scales. The height and width of the available bone in the implant area were estimated by using the detected bounding box attributes. The AB and MC detection performances using Dental-YOLO reached a mean average precision of 99.46%. The two-way analysis of variance (ANOVA) test showed no difference in the bone height and width measurements produced by the proposed approach and manual measurement by radiologists. Our results suggest that the Dental-YOLO detection system could be helpful for dental implant surgery and presurgical treatment planning.
Item Type: | Article |
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Uncontrolled Keywords: | Alveolar bone, CBCT, bone measurement, dental implant planning, mandibular canal, object detection, YOLO. |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RK Dentistry |
Divisions: | Faculty of Engineering > Department of Informatic |
Depositing User: | Monica Widiasri 61151 |
Date Deposited: | 03 Jan 2023 03:50 |
Last Modified: | 10 Jan 2023 03:48 |
URI: | http://repository.ubaya.ac.id/id/eprint/43044 |
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