Publications by authors named "Dhanaporn Papasratorn"
Objectives: To validate a novel artificial intelligence (AI)-based tool for automated tooth modelling by fusing cone beam computed tomography (CBCT)-derived roots with corresponding intraoral scanner (IOS)-derived crowns.
Methods: A retrospective dataset of 30 patients, comprising 30 CBCT scans and 55 IOS dental arches, was used to evaluate the fusion model at full arch and single tooth levels. AI-fused models were compared with CBCT tooth segmentation using point-to-point surface distances-reported as median surface distance (MSD), root mean square distance (RMSD), and Hausdorff distance (HD)- alongside visual assessments.
Article Synopsis
- - The study aimed to develop deep learning models for detecting the relationship between mandibular third molars and the inferior alveolar canal using panoramic radiographs, evaluating various data augmentation techniques.
- - A total of 1,800 cropped images were classified and analyzed using three pretrained models (AlexNet, VGG-16, and GoogLeNet), with training data increased through different levels of augmentation.
- - Results showed all models performed well, particularly VGG-16, with ten-fold augmentation yielding the best overall accuracy, while the quality of original data and its labeling was crucial for model effectiveness.