NICE: Neural Implicit Craniofacial Model for Orthognathic Surgery Prediction
Jiawen Yang, Yihui Cao, Xuanyu Tian, Yuyao Zhang, Hongjiang Wei

TL;DR
NICE is a neural implicit model that accurately predicts postoperative facial appearance after orthognathic surgery by modeling complex skeletal and soft tissue interactions with high precision.
Contribution
The paper introduces NICE, a novel implicit neural model that captures nonlinear biomechanical responses for improved surgical outcome prediction.
Findings
Outperforms existing methods in prediction accuracy
Improves modeling of lips and chin regions
Robustly preserves anatomical structures
Abstract
Orthognathic surgery is a crucial intervention for correcting dentofacial skeletal deformities to enhance occlusal functionality and facial aesthetics. Accurate postoperative facial appearance prediction remains challenging due to the complex nonlinear interactions between skeletal movements and facial soft tissue. Existing biomechanical, parametric models and deep-learning approaches either lack computational efficiency or fail to fully capture these intricate interactions. To address these limitations, we propose Neural Implicit Craniofacial Model (NICE) which employs implicit neural representations for accurate anatomical reconstruction and surgical outcome prediction. NICE comprises a shape module, which employs region-specific implicit Signed Distance Function (SDF) decoders to reconstruct the facial surface, maxilla, and mandible, and a surgery module, which employs…
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Taxonomy
TopicsOrthodontics and Dentofacial Orthopedics · Temporomandibular Joint Disorders · Dental Radiography and Imaging
