An integrated method for hemorrhage segmentation from brain CT Imaging
An integrated method for hemorrhage segmentation from brain CT Imaging
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DOI：
10.1016/j.compeleceng.2013.04.010
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发表时间：
2013-07-01
影响因子：
4.3
通讯作者：
Dewal, M. L.
中科院分区：
文献类型：
--
作者：
Bhadauria, H. S.;Singh, Annapurna;Dewal, M. L.
结合模糊C均值(FCM)聚类和基于区域的活动轮廓法的特点，提出了一种综合的分割方法。在该方法中，首先使用FCM聚类法对出血区域周围的轮廓进行初始化，然后基于区域的活动轮廓方法将初始轮廓传播到出血边界。此外，还利用FCM聚类自适应地估计给定图像的轮廓传播控制参数。基于区域的活动轮廓法利用传统的基于区域的活动轮廓法中局部区域相对于全局区域的强度信息来指导轮廓运动。在20例100幅出血性脑CT图像上测试了该方法的有效性，并与区域生长法、FCM聚类法和Chan&Vese方法进行了比较。该方法得到的相似性指数的平均值分别为79.93%、99.10%、84.83%和88.84%。(C)2013爱思唯尔有限公司。保留所有权利。
This paper presents an integrated segmentation method which combines the features of Fuzzy C-Mean (FCM) clustering and region-based active contour method. In the proposed method, FCM clustering is used to initialize the contour around the hemorrhagic region and then region-based active contour method propagates the initial contour towards the hemorrhage boundaries. Further, the FCM clustering is also used to estimate the contour propagation controlling parameters adaptively from the given image. The region-based active contour method uses the intensity information in the local regions as against the global regions in the traditional region-based active contour methods to guide the contour motion. The effectiveness of the proposed method is tested on the dataset of total 100 hemorrhagic brain CT images of 20 patients and the results are compared with region growing, FCM clustering and Chan & Vese methods. The proposed method yields the higher average values of the similarity indices namely sensitivity, specificity, accuracy and overlap metric as 79.93%, 99.10%, 84.83% and 88.84% respectively. (C) 2013 Elsevier Ltd. All rights reserved.