Elaboration of an Algorithm of Automated Segmentation by Magnetic Resonance Imaging for Bone and Muscles of Shoulder
试验速览
- 阶段
- 不适用
- 状态
- 撤回
- 入组人数
- 100
- 主要终点
- Algorithm developement
研究概览
简要总结
The primary objective of the study is to develop an algorithm of automated segmentation of shoulder by MRI examinations.
详细描述
This is a national monocentric study which will be conducted in Ambroise Paré hospital of APHP, in orthopaedics department (for enrollment) and radiological department (for CT-scan and MRI examinations) respectively.
Manual segmentations of 5 muscles and 2 bones of shoulder by MRI with automated segmentation of shoulders corresponding to CT-scan imagings.
3D imagings of each shoulder by manual segmentations from MRI and automated segmentation from computed tomography will provide to build a network.
The perspective of the elaborated algorithm should lead to an automated 3D-reconstruction of patients' shoulder as a routine care in surgery.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Other
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Healthy volunteer > 18 years, presenting any symptom nor history of shoulder pathology;
- •Affiliated to social security scheme.
排除标准
- •Symptoms or history of shoulder pathologies;
- •Claustrophobia;
- •Pregnant woman;
- •Patient covered by AME system;
- •Contre-indication to perform MRI examination (implant, less 6-months stent implantation, recent surgery, renal insufficiency, pace maker implantation, cardiac defibrillator, cardiovascular catheter, neurostimulation, implantable electronic pompe for automatic injection of medications).
结局指标
主要结局
Algorithm developement
时间窗: through study completion, an average of 8 month
The developement for automatic segmentation algorithm: uses method with a convolutional neural networks (convolutional neural network - CNN).
次要结局
未报告次要终点