ISSN 1004-4140
CN 11-3017/P
王海波, 李雪耀. 基于FCM聚类算法的颅内出血CT图像分割[J]. CT理论与应用研究, 2009, 18(2): 99-105.
引用本文: 王海波, 李雪耀. 基于FCM聚类算法的颅内出血CT图像分割[J]. CT理论与应用研究, 2009, 18(2): 99-105.
shu
WANG Hai-bo, LI Xue-yao. Segmentation of Intracranial Hemorrhage CT Image Based on FCM Clustering Algorithm[J]. CT Theory and Applications, 2009, 18(2): 99-105.
Citation: WANG Hai-bo, LI Xue-yao. Segmentation of Intracranial Hemorrhage CT Image Based on FCM Clustering Algorithm[J]. CT Theory and Applications, 2009, 18(2): 99-105.
shu

基于FCM聚类算法的颅内出血CT图像分割

Segmentation of Intracranial Hemorrhage CT Image Based on FCM Clustering Algorithm

    摘要
  • 摘要: 为了提高计算机辅助诊断系统的颅内出血病灶分割准确率,提出一种新的颅脑CT图像分割方法,被怀疑为出血的区域可快速而有效地分割出来。首先利用颅内结构提取算法提取颅内区域;然后利用两次模糊c均值聚类算法完成出血区域分割。第一次模糊c均值聚类确定疑似颅内出血的区域,根据脑出血CT图像特点,将中心点灰度值最高的类作为第二次模糊c均值聚类对象,第二次模糊c均值聚类分割出疑似出血区域,最后对颅脑CT图像进行实验,验证方法的可行性。实验结果表明该方法对颅脑出血CT图像病灶的分割是有效的。

     

    Abstract: To develop a computer aided detection system that improves diagnostic accuracy of intracranial hemorrhage(IH) on brain CT.A novel method for CT image segmentation of brain is proposed, with which, several regions that are suspicious of hemorrhage can be segmented rapidly and effectively.Algorithm of extracting intracranial area was introduced firstly to extract intracranial area.Secondly, FCM was employed twice, we named it with TFCM.FCM was first employed to identify areas of intracranial hemorrhage.Finally, FCM was employed to segment the lesions.Experimental results on real medical images demonstrate the efficiency and effectiveness of the proposed algorithm.

     

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