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基于目标检测的肺癌早期智能筛查系统的设计

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设计了一种基于目标检测的肺癌早期智能筛查系统,其运用YOLOv5s模型对去噪后肺CT图像中的肺结节进行目标检测,以实现肺癌早期的智能筛查.数据分析显示,试验的准确率、召回率无线接近于 1,证明了肺结节检测的准确率较高,验证了肺癌早期智能筛查系统的可靠性.该系统既能降低医师的工作难度,又能提升肺癌诊断的准确率,可成为辅助肺癌早期诊断的重要工具.
Design of Early Intelligent Screening System for Lung Cancer Based on Target Detection
A lung cancer early intelligent screening system based on object detection was designed,which uses the YOLOv5s model to detect lung nodules in denoised lung CT images,in order to achieve early intelligent screening of lung cancer.Data analysis shows that the accuracy and recall of the experiment are close to 1,which proves the high accuracy of lung nodule detection and verifies the reliability of the early intelligent screening system for lung cancer.This system can not only reduce the workload of physicians,but also improve the accuracy of lung cancer diagnosis,making it an important tool to assist in the early diagnosis of lung cancer.

pulmonary noduleimage denoisingtarget detectionYOLOv5s model

张春茜、刘华康、任俊龙、栗梦媛、张丽娟、回振桥

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河北水利电力学院电气自动化系,河北沧州 061001

河北省沧州中西医结合医院感染性疾病科,河北沧州 061001

肺结节 图像去噪 目标检测 YOLOv5s模型

2022年河北省教育厅科学研究项目资助

ZC2022018

2024

自动化应用
重庆西南信息有限公司

自动化应用

影响因子:0.156
ISSN:1674-778X
年,卷(期):2024.65(2)
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