CT图像肺结节计算机辅助检测与诊断技术研究综述  

Reviews on Computer-Aided Detection and Diagnosis of Pulmonary Nodules in CT Images

作　　者：伍长荣[1] 接标[1] 叶明全[2] 

机构地区：[1]安徽师范大学数学计算机科学学院,芜湖241002 [2]皖南医学院计算机教研室,芜湖241002

出　　处：《数据采集与处理》2016年第5期868-881,共14页Journal of Data Acquisition and Processing

基　　金：国家自然科学基金(61672386;61573023)资助项目;教育部人文社会科学研究规划基金(16YJAZH071)资助项目;安徽高校省级自然科学研究重点基金(KJ2016A275;KJ2014A266)资助项目

摘　　要：肺结节计算机辅助诊断(Computer-aided diagnosis,CAD)能够从CT图像中检测、分割和诊断肺结节,提高早期肺癌的生存率,因而具有重要临床意义。由于肺结节的形态根据其类型、尺寸、位置、内部结构及恶性与否等动态变化,导致肺结节检测和诊断已经成为一个重大的挑战问题。本文对比分析了CAD系统中肺实质分割、肺结节检测、肺结节分割以及肺结节良恶性判断等4个步骤所运用的关键技术及挑战,并指出开发有效CAD系统需要进一步优化不同类型结节诊断算法灵敏度、降低结节检测误报数量、提高诊断自动化水平,同时需要集成影像存储与通信系统(Picture archiving and communication systems,PACS)以及电子病历系统(Electronic medical record systems,EMRS),以便在日常临床实践中应用。Computer-aided diagnosis（CAD）system can detect,segment and diagnose pulmonary nodules from CT images,and improve the survival rate of early lung cancer,which has important clinical significance.As the appearance of pulmonary nodules varies with its type,size,location,internal structure,and malignancy,nodule detection and diagnosis have become a major challenge.Here the key techniques and challenges are analyzed in four main processing stages：segmentation of lungs from chest images,detection of pulmonary nodules inside the lung fields,pulmonary nodule segmentation,and diagnosis of pulmonary nodules as benign or malignant.Further research is needed to optimize the diagnosis algorithm sensitivity of nodules with different sizes and shapes,thus decreasing the number of false positives,and improving automation level of diagnosis.Finally,the picture archiving and communication systems（PACS）should be integrated with electronic medical record systems（EMRS）in order to be adopted in clinical practice.

关 键 词：CT图像 肺结节 计算机辅助检测与诊断 医学图像处理与分析 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]