G. Rubiu, M. Bologna, M. Cellina, M. Cè, D. Sala, R. Pagani, E. Mattavelli, D. Fazzini, S. Ibba, S. Papa, M. Alì

Teeth Segmentation in Panoramic Dental X-ray Using Mask Regional Convolutional Neural Network

Analisi di Immagini Medicali e Diagnostica Machine Learning Deep Learning

Convolutional Neural Network (CNN) models are capable of learning complex patterns and features from images. An automatic teeth segmentation CNN model can accurately and efficiently identify the boundaries and contours of individual teeth in dental radiographs or 3D dental scans. This can save significant time and effort compared to manual segmentation by dental professionals. Precise segmentation of teeth can assist in the diagnosis and treatment planning process. By accurately identifying the boundaries of teeth, dental practitioners can more effectively analyze dental conditions, such as tooth decay, gum diseases, or orthodontic abnormalities. This enables them to make informed decisions regarding appropriate treatment options and personalized treatment plans.

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