Title: Dental caries segmentation and detection using SIU-Net with YOLO v8 on CBCT images

Authors: Thankappan Swarnamma Pradeep; Arul Linsely Justus

Addresses: Department of Electronics and Communication Engineering, Noorul Islam Centre for Higher Education, Thuckalay, Kumaracoil, Tamil Nadu 629180, India ' Department of Electrical and Electronics Engineering, Noorul Islam Centre for Higher Education, Thuckalay, Kumaracoil, Tamil Nadu 629180, India

Abstract: Dental caries is one of the most prevalent and persistent illnesses globally. For radiologists, dental CBCT is an essential diagnostic tool. CBCT is widely used, but diagnosing dental caries remains challenging due to limited datasets and time-consuming annotation processes. To tackle these problems, a novel approach utilising a single input U-Net integrated with YOLO v8 for dental caries segmentation and detection is introduced. The proposed SIU-Net incorporates a multi-scale spatial attention module (MSAM), which enhances the model's ability to focus on critical tooth structures while suppressing irrelevant information, thereby improving the accuracy of caries segmentation. The efficient multiscale channel attention (EMCA) module effectively connects the encoder and decoder of the SIU-Net, facilitating better feature fusion. Furthermore, YOLO v8 is employed in this framework for precise tooth disease detection. This model is rigorously evaluated on CBCT images, and experimental results demonstrate that the proposed approach achieved a dice coefficient of 92%, IoU of 90%, precision of 92%, and accuracy of 94% to show its superior performance in accurately detecting dental caries compared to other state-of-the-art approaches. This proposed model makes significant advancements in dental caries detection and robustness across several dental imaging modalities.

Keywords: dental caries; single input U-Net; You Only Look Once Version 8; multi-scale spatial attention module; MSAM; efficient multiscale channel attention; EMCA; cone beam computed tomography; CBCT.

DOI: 10.1504/IJIEI.2026.151799

International Journal of Intelligent Engineering Informatics, 2026 Vol.14 No.1, pp.81 - 108

Received: 13 Jul 2024
Accepted: 20 Sep 2024
Published online: 20 Feb 2026 *

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