粗糙集方法在医学影像诊断分析中的应用  

The Application of Rough Set Method in Medical Imaging Diagnostic Analysis

作　　者：孙静[1] 孙兴旺[2] 

机构地区：[1]西安医学院医学技术系,陕西西安710021 [2]西安交通大学医学院附属第一医院,陕西西安710061

出　　处：《统计与信息论坛》2012年第6期83-87,共5页Journal of Statistics and Information

摘　　要：医学诊断常面对越来越多的医学影像数据信息,比较不同分析方法对于疾病诊断十分必要。对183例脑胶质瘤的MR资料分别使用粗糙集理论和logistic回归分析方法导出影像诊断规则。与病理结果对比后发现,使用粗糙集理论的诊断规则准确性高于其他统计方法。粗糙集理论对提高医学影像学诊断水平有更好的临床应用价值。Facing more and more medical image data information, it is necessary to compare different analysis method for disease diagnosis. This article analysis 183 cases of glioma MR details using rough sets theory and logistic regression analysis separately and work out the diagnosis rules. Comparing with pathological results, it can be found that rough set theory has higher diagnosis accuracy than the other statistical method. The rough set theory has better clinical application value to improve medical imaging diagnostic level.

关 键 词：粗糙集 医学影像 诊断规则 

分 类 号：O213[理学—概率论与数理统计]