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BP神经网络在肝癌数字减影血管造影诊断中的应用
引用本文:唐静波,龙学颖,刘彤,任力锋,曹觉,谢江平,彭健,张阳德. BP神经网络在肝癌数字减影血管造影诊断中的应用[J]. 中华生物医学工程杂志, 2009, 15(1). DOI: 10.3760/cma.j.issn.1674-1927.2009.01.012
作者姓名:唐静波  龙学颖  刘彤  任力锋  曹觉  谢江平  彭健  张阳德
作者单位:1. 中南大学卫生部肝胆肠外科研究中心,长沙,410008
2. 中南大学湘雅医院放射科
3. 中南大学生物医学工程研究院
基金项目:国家自然科学基金,中南大学研究生学位论文创新选题项目
摘    要:目的 探讨利用BP神经网络对肝癌数字减影血管造影(DSA)图像进行计算机辅助诊断的应用价值.方法 分析32例肝癌病例DSA影像资料,应用BP神经网络建立计算机临床辅助诊断模型,然后把100个随机抽样测试样本(非病灶样本55个,病灶样本45个)输入模型验证诊断准确率.结果 肝癌计算机辅助诊断模型成功建立,100个随机抽样样本经模型分析,真阳性率为91%,真阴性率95%.结论 BP神经网络可应用于临床辅助肝癌DSA诊断.

关 键 词:癌,肝细胞  数字减影血管造影  BP神经网络  诊断,计算机辅助  模型,神经网络

Application of hepatic carcinoma diagnosis with digital subtraction angiography images by back propagation neural network analysis
TANG Jing-bo,LONG Xue-ying,LIU Tong,liEN Li-feng,CAO Jue,XIE Jiang-ping,PENG Jian,ZHANG Yang-de. Application of hepatic carcinoma diagnosis with digital subtraction angiography images by back propagation neural network analysis[J]. Chinese Journal of Biomedical Engineering, 2009, 15(1). DOI: 10.3760/cma.j.issn.1674-1927.2009.01.012
Authors:TANG Jing-bo  LONG Xue-ying  LIU Tong  liEN Li-feng  CAO Jue  XIE Jiang-ping  PENG Jian  ZHANG Yang-de
Abstract:Objective To explore the value of computer-aided diagnosis of hepatic carcinoma with digital subtraction angiography (DSA) images by back propagation (BP) neural network. Methods DSA images of 32 cases with hepatic carcinoma were analyzed. According to the analysis results, computer-aided diagnostic model by using BP neural network was established. Then 100 random cases (55 cases without lesion, 45 cases with lesion) were input to verify diagnosis accuracy of the model. Results Computer-aided diagnostic model of hepatic carcinoma was established successfully. One hundred random sample data were analyzed by the model. The true positive rate was 91%, and the true negative rate was 95%. Conclusion BP neural network can be used as an assisted method for DSA diagnosis of hepatic carcinoma.
Keywords:Carcinoma,hepatocellular  Digital subtraction angiography  Back propagationneural network  Diagnosis,computer-assisted  Models,neural network
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