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作 者:吴双豆 柏艳红 唐中才 郭建康 WU Shuangdou;BAI Yanhong;TANG Zhongcai;GUO Jiankang(Department of Ultrasound Medicine,3201 Hospital,Hanzhong Shaanxi 723000,China)
机构地区:[1]三二〇一医院超声医学科,陕西汉中723000
出 处:《中国医疗设备》2025年第4期55-60,共6页China Medical Devices
摘 要:目的提出一种多模态超声诊断方法,将深度学习与多模态超声成像技术相结合,以进一步提高多模态超声成像技术在肝脏疾病诊断中的应用价值,实现更高精度的疾病诊断。方法研究首先引入边缘感知理念,提出了一种图像分割网络框架;通过训练得到图像分割模型,并对多模态超声图像进行预处理;再以支持向量机为基分类器,结合多模态超声图像的自身特征建立多个基分类器;最后根据信息熵、离散度以及均值方差比确定基分类器的系数,得到融合后的多模态超声诊断结果。结果研究结果表明,结合深度学习方法进行的多模态超声成像诊断模型的诊断准确度达到了95.78%,假阳性率和假阴性率分别为4.23%和4.50%,F1得分达到了0.93,Kappa统计量达到了0.92,具有较高的诊断精度。结论本研究提出的多模态超声诊断方法在肝脏疾病诊断中具有较高的应用价值,可帮助医师确定患者患病情况。Objective To propose a multimodal ultrasound diagnosis method,which combines deep learning with multimodal ultrasound imaging technology,in order to further improve the application value of multimodal ultrasound imaging technology in the diagnosis of liver diseases,and achieve higher precision disease diagnosis.Methods Firstly,the concept of edge perception was introduced,and a network framework for image segmentation was proposed.The image segmentation model was obtained by training,and the multi-modal ultrasound images were preprocessed.Then,support vector machine(SVM)was used as the base classifier,and multiple base classifiers were established by combining the characteristics of multimodal ultrasound images.Finally,the coefficients of the base classifiers were determined according to the information entropy,dispersion and mean-variance ratio,and the fused multimodal ultrasound diagnosis results were obtained.Results The research results showed that the diagnostic accuracy of the multi-modal ultrasonic imaging diagnostic model combined with deep learning method reached 95.78%,the false positive rate and false negative rate were 4.23%and 4.50%respectively,F1 score reached 0.93,and Kappa statistic reached 0.92,with high diagnostic accuracy.Conclusion The multimodal ultrasound diagnosis method proposed in this study has high application value in the diagnosis of liver diseases,which can help doctors to determine the disease status of patients.
关 键 词:多模态 超声成像 肝脏疾病 诊断 图像分割 分类 支持向量机
分 类 号:R197.39[医药卫生—卫生事业管理] TP391[医药卫生—公共卫生与预防医学]
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