Penerapan Model U-Net untuk Segmentasi Gigi pada Citra Radiografi Panoramik Orang Dewasa - Sonia, Sonia; Yohannes, Yohannes (Algoritme Jurnal Mahasiswa Teknik Informatika, 2025)
Dental and oral health play a crucial role in maintaining overall bodily health. Panoramic radiography serves as a primary diagnostic tool for analyzing dental and oral conditions; however, the complexity of its images often complicates manual analysis. This study aims to implement a Convolutional Neural Network (CNN) architecture for segmenting panoramic radiographic images, utilizing U-Net as the chosen model. The dataset used consists of panoramic radiographic images. The test results indicate that the implemented model achieved an IoU score of 0.8335 and a dice coefficient of 0.9092, demonstrating strong segmentation capability. These findings suggest that the proposed method can serve as a supportive tool for diagnosis and treatment planning in dental and oral healthcare.