用多视角图像和CT数据构建高精度静态数字人脊柱模型，助力青少年特发性侧弯动态研究
The establishment of static digital humans and the integration with spinal models
- 结合3D高斯与SMPL模型从多视角图像生成人体点云
- 脊柱模型与标准骨骼对齐，误差小于1度（以Cobb角为指标）
- 为脊柱动态仿真提供精准静态基础，适合临床与数字医学研究者
青少年特发性脊柱侧弯（AIS）是一种常见脊柱畸形，严重影响健康与生活质量。传统影像技术如X光、CT和MRI仅能提供静态脊柱图像，难以捕捉脊柱在日常活动中的动态变化及其与全身运动的交互关系。因此，发展新方法克服这些局限至关重要。动态数字人建模是数字医学的重大突破，可实现日常活动中脊柱三维动态可视化，帮助临床发现静态影像遗漏的畸形。尽管动态建模潜力巨大，但构建高精度静态数字人模型是后续研究的关键前提。本研究聚焦于整合脊柱的精准静态数字人建模，为后续AIS动态数字人研究奠定基础。首先，利用3D高斯与Skinned Multi-Person Linear（SMPL）模型，结合患者多视角图像生成人体点云数据；随后，将标准骨骼模型拟合至生成的人体模型；再将由CT重建的真实脊柱模型与标准骨骼模型对齐。通过六名AIS患者的X光片数据验证，以Cobb角（评估侧弯严重程度的指标）为评价标准，结果显示模型误差控制在1度以内。该研究提出了一种重要的数字人构建方法。
原文摘要 · Abstract (English)
Adolescent idiopathic scoliosis (AIS), a prevalent spinal deformity, significantly affects individuals' health and quality of life. Conventional imaging techniques, such as X - rays, computed tomography (CT), and magnetic resonance imaging (MRI), offer static views of the spine. However, they are restricted in capturing the dynamic changes of the spine and its interactions with overall body motion. Therefore, developing new techniques to address these limitations has become extremely important. Dynamic digital human modeling represents a major breakthrough in digital medicine. It enables a three - dimensional (3D) view of the spine as it changes during daily activities, assisting clinicians in detecting deformities that might be missed in static imaging. Although dynamic modeling holds great potential, constructing an accurate static digital human model is a crucial initial step for high - precision simulations. In this study, our focus is on constructing an accurate static digital human model integrating the spine, which is vital for subsequent dynamic digital human research on AIS. First, we generate human point - cloud data by combining the 3D Gaussian method with the Skinned Multi - Person Linear (SMPL) model from the patient's multi - view images. Then, we fit a standard skeletal model to the generated human model. Next, we align the real spine model reconstructed from CT images with the standard skeletal model. We validated the resulting personalized spine model using X - ray data from six AIS patients, with Cobb angles (used to measure the severity of scoliosis) as evaluation metrics. The results indicate that the model's error was within 1 degree of the actual measurements. This study presents an important method for constructing digital humans.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。