MICCAI 2022 Daily – Wednesday

and could accurately simulate their movements following each upper and lower jaw movement. ” Daeseung found that balancing the accuracy and complexity of the simulation condition was the most challenging aspect. If it was too complex, it used too many computational resources. The realistic lip sliding effect was the perfect balance between accuracy and efficiency. Facial changes were simulated little by little, which made it more natural, and it demonstrated a significant improvement over previous methods, improving prediction accuracy around the lips in both quantitative and qualitative measures. Despite these positive results, FEM still presented some challenges, particularly regarding efficiency . It would take some time to prepare the model, and surgeons with hectic schedules would not be able to wait in front of a computer for a model to be printed. “ Scientifically, it was sound, but in reality, it was not clinically practical, ” James says. “ That is why we started thinking about the deep learning method, which is where Dr. Yan and his group come in. ” Pingkun ’ s group has been working on deep learning techniques, including direct image processing, image analysis, and image construction, for several years. The two groups have come together to work on this problem and have joint authorship of the paper. Daeseung and Xi are co-first authors, and James and Pingkun are co- corresponding authors. It is a marriage of the clinical and the technical . 6 DAILY MICCAI Wednesday Oral Presentation