[1]张 琦,杜丽娟,唐 震.结合X线和超声的神经网络在乳腺检查的应用[J].医学信息,2018,31(13):9-12.[doi:10.3969/j.issn.1006-1959.2018.13.003]
　ZHANG Qi,DU Li-juan,TANG Zhen.Application of Neural Network Combined with X-ray and Ultrasound in Breast Examination[J].Journal of Medical Information,2018,31(13):9-12.[doi:10.3969/j.issn.1006-1959.2018.13.003]
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结合X线和超声的神经网络在乳腺检查的应用()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
31卷
期数:
2018年13期
页码:
9-12
栏目:
出版日期:
2018-07-01

文章信息/Info

Title:
Application of Neural Network Combined with X-ray and Ultrasound in Breast Examination
文章编号:
1006-1959（2018）13-0009-04
作者:
张 琦1; 杜丽娟1; 唐 震2
1.上海浦南医院影像科，上海 200125； 2.上海交通大学附属第六人民医院南院影像科，上海 201499
Author(s):
ZHANG Qi1; DU Li-juan1; TANG Zhen2
1.Department of Radiology,Shanghai Punan Hospital,Shanghai 200125,China; 2.Department of Radiology,South Hospital,Sixth People's Hospital Affiliated to Shanghai Jiao Tong University,Shanghai 201499,China
关键词:
神经网络; X线钼靶摄影; 超声检查; 乳腺病变
Keywords:
Key words：Neural network; X-ray mammography; Ultrasonography; Breast lesions
分类号:
R737.9
DOI:
10.3969/j.issn.1006-1959.2018.13.003
文献标志码:
A
摘要:
目的 探讨神经网络方法在鉴别乳腺X线和超声检查中良恶性病变的意义。方法 对75例乳腺疾病患者的X线钼靶及超声检查的数据用NN进行分析，随机选择30例样本作为训练样本，组成训练集，其余样本组成测试集。建立NN模型，分析神经网络模型的诊断结果。结果 75例患者中，手术与病理证实乳腺恶性病变44例，乳腺良性肿瘤或肿瘤样病变31例，钼靶X线诊断的特异度、敏感度及诊断正确率分别为90.32%、88.64%和89.33%，B超诊断的特异度、敏感度及诊断正确率分别为87.09%、86.36%和86.67%，X线钼靶和B超对比，差异无统计学意义（P＞0.05）。而BP网络的特异度为95.45%，敏感度为95.65%，总正确率为95.56%，高于X线钼靶和B超，差异具有统计学意义（P＜0.05）。结论 神经网络具有人脑的学习、不断进步的优点，又比人脑客观，结合X线钼靶和B超检查的神经网络在判断乳腺良恶性病变性质方面有一定的应用价值。
Abstract:
Abstract：Objective To explore the significance of neural network in the differential diagnosis of benign and malignant lesions in X-ray mammography and ultrasonography.Methods The data of X-ray mammography and ultrasonography in 75 patients with breast disease were analyzed by NN.30 samples were randomly selected as training samples to form a training set,and the remaining samples were composed of test sets.Establish a NN model and analyze the diagnosis results of the neural network model.Results Among the 75 cases,44 cases of malignant breast lesions,31 cases of benign breast tumor or tumor like lesion were confirmed by operation and pathology.The specificity,sensitivity and diagnostic accuracy of molybdenum target X-ray diagnosis were 90.32%,88.64% and 89.33% respectively.The specificity, sensitivity and diagnostic accuracy of B ultrasonic diagnosis were 87.09%,86.36% and 86.67%, respectively,there was no significant difference between X-ray mammography and B-ultrasound(P>0.05).The specificity of BP network was 95.45%,the sensitivity was 95.65%,and the total correct rate was 95.56%,which was higher than that of X-ray mammography and B-mode ultrasound,the difference was statistically significant(P<0.05).Conclusion Neural network has the advantages of learning and continuous improvement of human brain.It is more objective than human brain.The neural network combined with X-ray mammography and B-ultrasound has certain application value in judging the nature of benign and malignant breast lesions.

参考文献/References:

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更新日期/Last Update: 2018-07-01