【摘要】 肺癌已成为危害人类健康的重大威胁,肺部肿瘤的精准分割是临床诊疗分析的基础,也是放射组学的重要步骤。本文提出了一种基于3D Dense U-net神经网络分割算法,该算法用于从肺部CT图像中准确地检测和分割肺肿瘤。实验结果表明本文方法能够精准分割出肺部CT图像中的肺肿瘤,满足临床诊断治疗和病理学分析研究的要求。更多还原

【Abstract】 Lung cancer has become a major threat to human health. The precise segmentation of lung tumors is the basis of clinical diagnosis and treatment analysis, as well as an important step in radiomics. This paper proposes a segmentation algorithm based on 3D Dense U-net neural network, which is used to accurately detect and segment lung tumors from lung CT images. Experimental results show that this method can accurately segment lung tumors in lung CT images, and meet the requirements of clinical diagnosis, treatment and pathological analysis.更多还原