期刊文献+

模糊聚类技术分割颅脑肿瘤MR图像的应用研究 被引量:3

Application study of cerebral neoplasms MR images segmentation using fuzzy clustering technology
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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。 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.
出处 《医学影像学杂志》 2009年第9期1091-1093,共3页 Journal of Medical Imaging
关键词 模糊C均值 图像分割 颅脑肿瘤 磁共振成像 Fuzzy C-mean Image segmentation Cerebral neoplasm Magnetic resonance imaging
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参考文献8

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二级参考文献4

共引文献50

同被引文献20

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