SBIR Phase I: Novel Artificial Intelligence (AI)-Mediated Orthopedic Implant Design and Selection
SBIR Phase I: Novel Artificial Intelligence (AI)-Mediated Orthopedic Implant Design and Selection
批准号:
2213118
负责人:
William Byron
金额:
$25.46万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-02-15 至 2024-08-31
中文摘要
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英文摘要
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.
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