SBIR Phase I: Novel Artificial Intelligence (AI)-Mediated Orthopedic Implant Design and Selection

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力是为受创伤性颌骨损伤和疾病影响的动物定制牙齿种植解决方案。尽管解剖结构、骨强度和操作要求存在较大差异，但目前的兽医植入物使用的是为人类设计的平台。这种方法存在解剖学和生理学上的缺陷，会导致创伤、新生血管损伤、不完全愈合以及无法改善或恢复功能。该项目提出了一个软件程序和系统，用于根据特定的解剖结构和程序生成定制的植入物设计和标准。一个成功的项目将改善兽医护理和宠物和服务犬受伤后的生活。这个小企业创新研究（SBIR）第一阶段项目旨在开发一种机器学习（ML）软件，将骨密度筛查与二维到三维重建软件结合起来，以创建解剖学衍生的植入物和软件引导的植入物放置。拟议的机器学习系统将确定关键的解剖学考虑因素和动物分类，以优化植入物设计和程序标准。通过整合适当的动物扫描数据库，机器学习软件将确定植入的最佳区域，并根据需要进行优化。第一阶段的结果是一个数据库衍生的算法，该算法生成种植体的形状和大小，避免了干扰正确放置的解剖特征。该奖项反映了美国国家科学基金会的法定使命，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 broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is customized dental implant solutions for animals affected by traumatic jaw injury and disease. Current veterinary implants utilize platforms designed for human use, despite a greater variability in anatomy, bone strength, and procedural requirements. This approach has subsequent shortcomings accounting for anatomical and physiologic variations resulting in trauma, neovascular damage, incomplete healing, and failure to improve or restore functionality. The project proposes a software program and system for generating customized implant designs and criteria based on the specific anatomy and procedure. A successful project would improve veterinary care and the lives of pets and service dogs following injury. This Small Business Innovation Research (SBIR) Phase I project aims to develop a Machine Learning (ML) software to incorporate bone density screening with 2-dimensional to 3-dimensional reconstruction software to create anatomically derived implants and software guided implant placement. The proposed ML system will identify key anatomical considerations and animal classifications for optimizing implant designs and procedural criteria. By integrating a database of appropriate animal scans, the ML software will identify the optimal regions for implant and refine as needed. The result of this Phase 1 is a database-derived algorithm which generates implant shapes and sizes that avoid anatomical features that interfere with proper placement.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.