Dental Periapical Lesion Detection with Retinex Image Processing and an Efficient Deep Learning Model
Dental periapical lesions help doctors understand your oral health needs and must be found accurately to deliver proper treatment. The research introduces a new way to find dental periapical lesions by combining Retinex image processing with YOLOv8 object detection. The Retinex method lets the model detect periapical lesions more accurately because it enhances image details while removing picture noise. Test outcomes show enhanced lesion detection that performs well with precise accuracy in tough image scenarios. The research demonstrates how advanced image processing helps medical imaging deep learning systems work better. The Objective of this work is to improve visibility of periapical lesions by Retinex based enhancement and fast detection through YOLOv8.
Authors
- Camilo Christo (ORCID: https://orcid.org/0000-0001-8610-0632)
- M. Deva Priya
- Julia Punitha Malar Dhas (ORCID: https://orcid.org/0000-0001-5563-8077)
Institutions
- Karunya University (IN)
Publication Details
- Published
- 2025-04-24
- DOI
- https://doi.org/10.1109/icoei65986.2025.11013512
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00