Assessment of the AI-assisted Registration Versus Conventional Point-based Registration on CBCTs With Heavy Metal Artifacts
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 入组人数
- 16
- 试验地点
- 1
- 主要终点
- Registration accuracy
研究概览
简要总结
Our study investigates the accuracy and duration needed for 3D model registration using artifical intelligence (AI) assistance compared to conventional point-based registration. Manual segmentation of all cone beam computed tomography (CBCT) scans will be performed before the registration procedure.
详细描述
CBCT images and intraoral scans will be screened following specific eligibility criteria. 16 CBCT images and intraoral scans that will meet the inclusion criteria will undergo manual segmentation via 3D medical image processing software. Afterward, point-based registration and AI-assisted registration will be performed by a single operator using specialized implant planning software. Then, the registration accuracy will be examined by measuring the distances between the three-dimensional models of CBCT data and intraoral scans. Also, the duration required for registration will be calibrated and recorded by a stopwatch.
研究设计
- 研究类型
- Interventional
- 分配方式
- Non Randomized
- 干预模型
- Parallel
- 主要目的
- Other
- 盲法
- None
入排标准
- 年龄范围
- 15 Years 至 —（Child, Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •CBCT scans for either the maxilla or mandible or both and intraoral scans or manual impressions with metal restorations.
排除标准
- •Scans without metal restorations.
结局指标
主要结局
Registration accuracy
时间窗: immediately after the procedure
Distance between registered 3d model and CBCT in millimeters
次要结局
- Duration for registration(During the procedure)
研究者
Nehal Ibrahim Ahmed Shobair
principal investigator
Ain Shams University