The Role of CNN Architecture-based Transfer Learning of Medical Imaging in Lung Cancer Diagnosis and Staging
试验速览
- 阶段
- 不适用
- 发起方
- 入组人数
- 500
- 试验地点
- 1
- 主要终点
- pathologic result revealed cancer cell involvement in lesion
研究概览
简要总结
Lung cancer diagnosis and staging are two fundamental and critical issue in clinical lung cancer management and therapeutic decision-making. Invasive procedures for pathologic analysis are gold standard for diagnosis and staging, however, invasive procedures related-complications are inevitable. Noninvasive medical imaging is a powerful tool, however there is almost no room for improvement just according to the experience of radiologist and clinician. The researchers will investigate the role of computer based deep learning of medical imaging in the diagnosis of lesion of lung, lymph node and other sites suspected with metastasis.
详细描述
Radiologist
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 75 Years(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Pathological diagnosis of lung cancer
- •PET/CT or CT examination before any cancer-specific treatment
排除标准
- •A history of other malignancies
结局指标
主要结局
pathologic result revealed cancer cell involvement in lesion
时间窗: 1 month after the pathologic test
次要结局
未报告次要终点
研究者
Yang Jin
Professor
Wuhan Union Hospital, China
