Affiliation:
1. State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases & Department of Orthodontics, West China Hospital of Stomatology Sichuan University Chengdu China
2. National Key Laboratory of Fundamental Science on Synthetic Vision Sichuan University Chengdu China
3. College of Mathematics Sichuan University Chengdu China
4. College of Computer Science Sichuan University Chengdu China
Abstract
AbstractObjectivesTo develop an artificial intelligence (AI) system for automatic palate segmentation through CBCT, and to determine the personalized available sites for palatal mini implants by measuring palatal bone and soft tissue thickness according to the AI‐predicted results.Materials and MethodsEight thousand four hundred target slices (from 70 CBCT scans) from orthodontic patients were collected, labelled by well‐trained orthodontists and randomly divided into two groups: a training set and a test set. After the deep learning process, we evaluated the performance of our deep learning model with the mean Dice similarity coefficient (DSC), average symmetric surface distance (ASSD), sensitivity (SEN), positive predictive value (PPV) and mean thickness percentage error (MTPE). The pixel traversal method was proposed to measure the thickness of palatal bone and soft tissue, and to predict available sites for palatal orthodontic mini implants. Then, an example of available sites for palatal mini implants from the test set was mapped.ResultsThe average DSC, ASSD, SEN, PPV and MTPE for the segmented palatal bone tissue were 0.831%, 1.122%, 0.876%, 0.815% and 6.70%, while that for the palatal soft tissue were 0.741%, 1.091%, 0.861%, 0.695% and 12.2%, respectively. Besides, an example of available sites for palatal mini implants was mapped according to predefined criteria.ConclusionsOur AI system showed high accuracy for palatal segmentation and thickness measurement, which is helpful for the determination of available sites and the design of a surgical guide for palatal orthodontic mini implants.
Funder
National Natural Science Foundation of China
Subject
Otorhinolaryngology,Oral Surgery,Surgery,Orthodontics
Cited by
2 articles.
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