基于深度学习的计算机辅助诊断系统在肺癌早期诊断中的应用与进展

Application and development of computer-aided diagnosis systems based on deep learning for the early diagnosis of lung cancer

胸部CT扫描是肺癌早期筛查和诊断的主要检查手段,应用于胸部影像诊断领域的基于深度学习的计算机辅助诊断(CAD)系统可对CT图像上的肺结节进行检测和分类。深度学习技术可提高CAD系统的性能,尤其是在提高肺结节检测的准确率和降低假阳性率方面。笔者就CAD系统中的深度学习模型在肺结节中的应用现状和研究进展作一综述。

Chest CT scan is the primary medical imaging method performed for the early screening and diagnosis of lung cancer.Deep-learning based computer aided diagnosis(CAD)system for chest CT imaging is helpful for detecting and classifying pulmonary nodules.Deep-learning techniques can improve the performance of CAD systems,especially in enhancing the accuracy of pulmonary nodule detection and reducing false-positive rates.This article reviewed the current application status of deep-learning models in CAD systems and the progress that has been achieved in using these systems for imaging pulmonary nodules.