CHS: Medium: Collaborative Research: Inverse Anatomical Modeling of the Face for Orthognathic Surgery

面孔是个体身份感和自尊的中心，在人际关系中起着至关重要的作用。当前的技术状态从两个不同的角度接近人脸的计算建模。计算机图形模型具有高度的视觉真实感，就像在电影中看到的那样。 而生物力学则侧重于物理现实主义，将面部建模为遵守物理定律的复杂机械系统。该项目将弥合这两个观点之间的差距，并构建提供视觉和物理现实主义的面部模型。这在诸如手术预测的应用中是极其重要的。近5%的美国人口有可能需要下巴手术的牙面异常，这可能对面部外观产生深远的影响。几乎每个病人都会问：“治疗后我会怎么看？“尽管这是一个重要且研究充分的问题，但目前还没有能够预测术后面部表情变化的方法。通过结合视觉和物理现实主义，这项研究将创建第一个系统，可以提供一个自然的，3D视觉回答病人的问题，通过显示逼真的面部动画后，模拟手术程序。其他广泛的影响将来自项目成果，因为用于生物材料有效模拟的新数值技术将提供可重复使用的基础，可用于表现出明显异质性和各向异性的各种工程材料的计算建模。在这项工作中开发的解剖建模框架也将作为一个发射台，为未来的调查感兴趣的医学科学（建模的软组织手术，探索老化或病理学的力学面部表情等）。为此，该项目将创建算法，用于自动开发精确的患者特定面部解剖模型，这些模型能够代表软组织的真实行为，包括面部表情的形成。该研究旨在应对需要跨学科协调努力的挑战，包括计算机图形学，计算机视觉，生物力学和颅面手术。新的计算机视觉方法将利用来自3D成像（MRI/CT）的信息来捕获活体人脸变形的细节。所采集的数据将作为有限元逆解算器的输入，该逆解算器将计算人特定软组织的未知力学参数，说明预应变和肌肉激活单元。这种以数据为中心的方法与现有的模型构建方法不同，有可能对解剖建模领域产生变革性的影响。此外，虽然正颌外科手术的临床应用被用作工作的动机和关键基准，但在这项活动中产生的算法创新超越了这项任务的特定范围，并在视觉计算和计算动力学领域提供了更广泛的实用性。基于物理的弹性物体的形状和变形模型将作为结构先验被纳入视觉采集系统，增强数据收集的鲁棒性和准确性。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The face is the center of an individual's sense of identity and self-esteem, and plays a crucial role in interpersonal relationships. The current state of the art approaches computational modeling of human faces from two distinct angles. Computer graphics models feature high visual realism, as seen in the movies. Whereas biomechanics focuses on physical realism, modeling the face as a sophisticated mechanical system that obeys the laws of physics. This project will bridge the gap between these two viewpoints and construct models of the face that offer both visual and physical realism. This is of the utmost importance in applications such as surgical prediction. Close to five percent of the population of the United States has a dentofacial anomaly that may require jaw surgery, which can have a profound effect on the appearance of the face. Virtually every patient asks, "How will I look after the treatment?" Even though this is an important and well-studied problem, there are currently no methods capable of predicting post-operative changes in facial expressions. By combining both visual and physical realism, this research will create the first system that can provide a natural, 3D visual answer to the patient's question by displaying a photorealistic facial animation after a simulated surgical procedure. Additional broad impact will derive from project outcomes because the new numerical techniques for the efficient simulation of biomaterials will provide a reusable foundation that can be leveraged for computational modeling of a variety of engineering materials that exhibit pronounced heterogeneity and anisotropy. The anatomical modeling framework developed in this work will also serve as a launchpad for future inquiry of interest to medical science (modeling of soft-tissue surgery, exploration of aging or pathology in the mechanics of facial expression, etc.).To these ends, the project will create algorithms for the automated development of accurate patient-specific models of facial anatomy capable of representing realistic behavior of soft tissues, including the formation of facial expressions. The research aims at challenges which require coordinated efforts across various disciplines, including computer graphics, computer vision, biomechanics and craniofacial surgery. Novel computer vision methods will leverage information from 3D imaging (MRI/CT) to capture details of in-vivo human face deformations. The acquired data will serve as input to inverse finite element solvers, which will compute the unknown mechanical parameters of person-specific soft tissues, accounting for pre-strain and muscle activation units. This data-centric approach is a departure from established model-building methodologies, and has the potential to make a transformative impact on the anatomical modeling field. Furthermore, although the clinical application of orthognathic surgery is used as the motivation and key benchmark for the work, the algorithmic innovations produced in this activity transcend the specific scope of this task and deliver broader utility in the fields of visual computing and computational dynamics. Physics-based models of shape and deformation of elastic objects will be incorporated into visual acquisition systems as structural priors, enhancing the robustness and accuracy of the data collection.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.