Predicting an Opaque Bubble Layer During Small-Incision Lenticule Extraction Surgery Based on Deep Learning
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 4,678
- 试验地点
- 1
- 主要终点
- The area of patients with opaque bubble layer in the SMILE surgeries
研究概览
简要总结
To explore the prediction of OBL by deep learning model in SMILE surgery
详细描述
The DL model was used to predict the OBL area during SMILE surgery by identifying the corneal full-view images before laser scanning. The DL model developed may assist surgeons to predict the possible OBL area of patients in advance, so as to adjust some surgical parameters and reduce the formation of OBL, which can avoid negative effects on surgeons' operation and patients' postoperative visual recovery, which has important practical significance.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Other
入排标准
- 年龄范围
- 18 Years 至 45 Years（Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •A condition in which the spherical equivalent refractive error of an eye is ≤ -0.50 D when ocular accommodation is relaxed;
- •Age ≥18 years;
- •Spherical equivalent (SE) ≥ -10.0D;
- •Corrected distance visual acuity (CDVA) ≥ 16/20;
- •Stable myopia for at least 2 years;
- •No contact lenses wearing for at least 2 weeks
排除标准
- •The presence or history of eye conditions other than myopia and astigmatism, such as keratoconus or external eye injury;
- •A history of eye surgery;
- •The presence or history of systemic diseases.
结局指标
主要结局
The area of patients with opaque bubble layer in the SMILE surgeries
时间窗: Day 0
The area of patients with opaque bubble layer were observed during the SMILE surgeries.
次要结局
- ResNet model(Day 0)
- Deep learning model(Day 0)
- U-net model(Day 0)
- Vgg19 model(Day 0)
研究者
Yifeng Yu
Deputy chief physician of Ophthalmology center of the Second Affiliated Hospital of Nanchang University
Second Affiliated Hospital of Nanchang University