12 citations · 25 across the 6 of their papers we have counts for
6 papers
PINNOCHIO: Physics-Informed Neural Network for Coupled Hyperelastic Interface-Volume Simulation in Orthognathic Surgery
Jungwook Lee, Daeseung Kim, Kevin Gu +6
Predicting patient-specific facial soft-tissue deformation is critical for iterative orthognathic surgery planning. However, current computational methods face a strict accuracy-ef…
Soft-tissue Driven Craniomaxillofacial Surgical Planning
Xi Fang, Daeseung Kim, Xuanang Xu +8
In CMF surgery, the planning of bony movement to achieve a desired facial outcome is a challenging task. Current bone driven approaches focus on normalizing the bone with the expec…
Deep Learning-based Facial Appearance Simulation Driven by Surgically Planned Craniomaxillofacial Bony Movement
Xi Fang, Daeseung Kim, Xuanang Xu +8
Simulating facial appearance change following bony movement is a critical step in orthognathic surgical planning for patients with jaw deformities. Conventional biomechanics-based…
Federated Cross Learning for Medical Image Segmentation
Xuanang Xu, Hannah H. Deng, Tianyi Chen +6
Federated learning (FL) can collaboratively train deep learning models using isolated patient data owned by different hospitals for various clinical applications, including medical…
SkullEngine: A Multi-stage CNN Framework for Collaborative CBCT Image Segmentation and Landmark Detection
Qin Liu, Han Deng, Chunfeng Lian +8
We propose a multi-stage coarse-to-fine CNN-based framework, called SkullEngine, for high-resolution segmentation and large-scale landmark detection through a collaborative, integr…
A Self-Supervised Deep Framework for Reference Bony Shape Estimation in Orthognathic Surgical Planning
Deqiang Xiao, Hannah Deng, Tianshu Kuang +11
Virtual orthognathic surgical planning involves simulating surgical corrections of jaw deformities on 3D facial bony shape models. Due to the lack of necessary guidance, the planni…