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模糊聚类技术分割颅脑肿瘤MR图像的应用研究
引用本文:段玉婷,张梦龙,姜玉芝,谢国华.模糊聚类技术分割颅脑肿瘤MR图像的应用研究[J].医学影像学杂志,2009,19(9):1091-1093.
作者姓名:段玉婷  张梦龙  姜玉芝  谢国华
作者单位:1. 山东省聊城市人民医院影像科,山东,聊城,252000
2. 山东省医学影像学研究所,山东,济南,250021
摘    要:目的:分析自编的模糊C均值(fuzzy cmeans,FCM)算法图像处理程序对颅脑肿瘤MRI图像的分割效果。方法:采集50幅不同脑肿瘤MRI平扫系列图像,用FCM程序对病灶自动分割,同时请影像学专家对相应病灶面积进行手工绘制,用重合率和误分割率两个指标进行比较分析两者的分割效果。结果:FCM程序分割病灶的重合率为91.2%,误分割率为10.8%。二者面积的差值无显著性差异(P〉0.05)。结论:FCM程序可以无监督地自动分割脑肿瘤MRI图像,有较强的临床应用价值。

关 键 词:模糊C均值  图像分割  颅脑肿瘤  磁共振成像

Application study of cerebral neoplasms MR images segmentation using fuzzy clustering technology
DUAN Yu-ting,ZHANG Meng-long,JIANG Yu-zhi,XIE Guo-hua.Application study of cerebral neoplasms MR images segmentation using fuzzy clustering technology[J].Journal of Medical Imaging,2009,19(9):1091-1093.
Authors:DUAN Yu-ting  ZHANG Meng-long  JIANG Yu-zhi  XIE Guo-hua
Institution:DUAN Yu-ting, ZHANG Meng-long, JIANG Yu-zhi, XIE Guo-hua ( 1. Department of Imaging, Liaocheng People' s Hospital, Shangdong Liaocheng 252000, P. R. China; 2. Shandong Medical Imaging Research Institute, Shandong Jinan 250021, P. R. China)
Abstract:Objective:To study the effects of fuzzy C-means(FCM) algorithm for image processing prepared by authors in the segmentation of cerebral neoplasms MR images.Methods:FCM was performed in 50 cases with different cerebral neoplasms MR images and compared to the hand-drawn images lesion areas by experts.The following indicators were extracted:coincidence rate,segmentation error rate,and analysed data.Results:The coincidence rate is 91.178% and the segmentation error rate is 10.8% by using FCM process.And no significant statistic differences ( P 〉 0.05) were shown between two areas. Conclusion: FCM procedure can be used as automatic and non-supervisory method in segrnentatior, of cerebral neoplasms MR images and it have a strong clinical value.
Keywords:Fuzzy C-mean  Image segmentation  Cerebral neoplasm  Magnetic resonance imaging
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