Review on Dental Image Segmentation Using Deep Learning Techniques
Author(s): 1.Dr.Reena M Roy,2. Aiswarya SS, 3.Archakrishna SS, 4.Fathima Shifana RH, 5.Lekshmi B
Authors Affiliations:
1.Assistant Professor, Dept. of ECE, LBS Institute of Technology for Women (Affiliated to APJ KTU)
2.B. Tech Student, Dept. of ECE, LBS Institute of Technology for Women(Affiliated to APJ KTU)
3.B. Tech Student, Dept. of ECE, LBS Institute of Technology for Women(Affiliated to APJ KTU)
4.B. Tech Student, Dept. of ECE, LBS Institute of Technology for Women(Affiliated to APJ KTU)
5.B. Tech Student, Dept. of ECE, LBS Institute of Technology for Women(Affiliated to APJ KTU)
DOIs:10.2015/IJIRMF/202502013 | Paper ID: IJIRMF202502013Accurate diagnosis, treatment planning, and advanced dental applications rely heavily on the effective segmentation of dental structures in imaging. Challenges such as low contrast, noise, and overlapping structures in dental X-rays make precise segmentation is a complex task. Recent advancements in deep learning have introduced innovative approaches that combine global context modeling with fine-grained spatial detail retention, addressing the limitations of traditional methods. Some techniques integrate multi-scale feature extraction, self-attention mechanisms, and specialized preprocessing strategies to improve segmentation accuracy and boundary delineation. This proposes a robust framework that synthesizes these advancements, focusing on enhancing segmentation performance for dental X-rays. By addressing unique challenges and leveraging the strengths of cutting-edge methodologies, the work aims to improve the precision, reliability, and clinical applicability of automated dental segmentation systems, contributing to more efficient diagnostics and treatment planning.
Dr.Reena M Roy, Aiswarya SS, Archakrishna SS, Fathima Shifana RH, Lekshmi B. (2025); International Journal for Innovative Research in Multidisciplinary Field, ISSN(O): 2455-0620, Vol-11, Issue-2, Pp.75-81. Available on – https://www.ijirmf.com/
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