基于贝叶斯网络的乳腺肿瘤超声诊断定量分析Quantitative Analysis for Ultrasound Diagnosis of Breast Tumors Based on Bayesian Network
黄金华;刘烁;苏福再;丁雪梅;杨洪钦;
摘要(Abstract):
利用贝叶斯网络建模方法,定量分析了1 500例良性肿瘤和500例恶性肿瘤临床乳腺肿瘤超声检查相关参量的诊断参考价值以及各参量之间的关联程度.研究结果表明,在超声检查中,形态检查参量的诊断价值最高(40.3%),其次分别为阻力指数(25.0%)、钙化灶(18.4%)和血流信号(16.3%)等检查参量.此外,阻力指数与血流信号之间的关联性比较强,约为0.432.贝叶斯概率模型在乳腺肿瘤超声智能诊断的前期应用研究,有助于帮助医生根据各检查参量诊断参考价值和各参量之间关联程度分析,实现乳腺肿瘤超声的智能诊断,提高诊断准确率.
关键词(KeyWords): 贝叶斯网络;乳腺肿瘤;超声检查;智能诊断
基金项目(Foundation): 国家重点基础研究发展计划(973计划,2015CB352006);; 国家自然科学基金重点资助项目(61335011)
作者(Authors): 黄金华;刘烁;苏福再;丁雪梅;杨洪钦;
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