基于深度学习的肺结节识别与检测研究

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1、单位代码10635学号112015333002108硕士学位论文基于深度学习的肺结节识别与检测研究论文作者：张金指导教师：段书凯教授学科专业：信号与信息处理研究方向：模式识别与深度学习提交论文日期：2018年04月17日论文答辩日期：2018年06月02日学位授予单位：西南大学中国∙重庆2018年6月LungNoduleRecognitionandDetectionBasedonDeepLearningAThesisSubmittedtoSouthwestUniversityinPartialFulfillmentoftheRequirementfortheMaster’sDegreeo

2、fEngineeringByZhangJinSupervisedbyProf.DuanShuKaiSpecialty:SignalandInformationProcessingCollegeofElectronicandInformationEngineeringofSouthwestUniversity,Chongqing,ChinaJune,2018目录摘要..................................................................................................................

3、.............IAbstract...........................................................................................................................III第一章引言..................................................................................................................11.1研究背景及意义...................

4、............................................................................11.2国内外研究现状...............................................................................................31.2.1深度学习研究现状................................................................................31.2.2肺结节识别与检测研究现状...

5、.............................................................41.3肺结节...............................................................................................................61.3.1X光胸片与CT肺结节..........................................................................61.3.2肺结节良恶性诊断..............

6、..................................................................71.4论文创新点.......................................................................................................71.5论文结构和安排...............................................................................................8第二章基于胶囊网络的良恶

7、性肺结节诊断..............................................................92.1良恶性肺结节数据集.......................................................................................92.2胶囊网络..........................................