[1]郭骁,杨冠羽,王征,等.基于Zernike矩和水平集的超声图像分割[J].东南大学学报(自然科学版),2015,45(2):247-250.[doi:10.3969/j.issn.1001-0505.2015.02.009]
 Guo Xiao,Yang Guanyu,Wang Zheng,et al.Ultrasound image segmentation based on Zernike moment and level set[J].Journal of Southeast University (Natural Science Edition),2015,45(2):247-250.[doi:10.3969/j.issn.1001-0505.2015.02.009]
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基于Zernike矩和水平集的超声图像分割()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
45
期数:
2015年第2期
页码:
247-250
栏目:
计算机科学与工程
出版日期:
2015-03-20

文章信息/Info

Title:
Ultrasound image segmentation based on Zernike moment and level set
作者:
郭骁杨冠羽王征舒华忠
东南大学影像科学与技术实验室, 南京210096
Author(s):
Guo Xiao Yang Guanyu Wang Zheng Shu Huazhong
Laboratory of Image Science and Technology, Southeast University, Nanjing 210096, China
关键词:
Zernike矩 相位 水平集 超声图像
Keywords:
Zernike moment phase level set ultrasonic image
分类号:
TP391
DOI:
10.3969/j.issn.1001-0505.2015.02.009
摘要:
为了提高超声图像的分割精确率,提出了一种基于Zernike矩和水平集的超声图像分割方法. 首先,利用9个具有不同阶数和重复度的Zernike矩提取超声图像的纹理特征,保留矩的幅值和相位,获得18个特征图,同时在每一特征图目标区域内外采样,利用采样值计算出特征图的权值.然后,将特征图与高斯算子进行卷积,计算其边缘检测函数,将所有特征图的边缘检测函数与对应的特征图权值相乘,所得结果之和即为该超声图像的边缘检测函数.最后,利用基于变分函数的水平集方法对超声图像进行分割. 基于前列腺超声图像的实验结果显示,相比基于梯度的水平集方法和基于Zernike矩幅值的水平集方法,所提方法具有更高的分割精度,dice相似系数达到95%以上.
Abstract:
To improve the segmentation accuracy of ultrasonic images, an ultrasonic image segmentation method based on the Zernike moments(ZMs)and the level set is presented. First, 9 ZMs with different orders and repetitions are used to extract the image features. Both the magnitudes and phases are reserved to obtain 18 feature images. Meanwhile, the weights of the feature images are calculated according to the samples obtained by sampling inside and outside of the target region of each feature image. Then, the edge indicator functions are calculated by the convolution of the feature images and the Gaussian operator. The sum of the multiplication results of the edge indicator functions and the corresponding weights of the feature images is the edge indicator function of the ultrasonic image. Finally, the ultrasonic image is segmented by the level set method based on the variation formulation. The experimental results of prostate ultrasonic images show that compared with the level set method based on the gradient and the level set method based on the ZM magnitude, the proposed method has higher segmentation accuracy, and the dice similarity coefficients are more than 95%.

参考文献/References:

[1] Belaid A, Boukerroui D, Maingourd Y, et al. Phase-based level set segmentation of ultrasound images [J]. IEEE Transactions on Information Technology in Biomedicine, 2011, 15(1): 138-147.
[2] Chan T F, Vese L A. Active contours without edges [J]. IEEE Transactions on Image Processing, 2001, 10(2): 266-277.
[3] Li C, Xu C, Gui C, et al. Level set evolution without re-initialization: a new variational formulation[C]//IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego, CA, USA, 2005, 1: 430-436.
[4] Chan T F, Sandberg B Y, Vese L A. Active contours without edges for vector-valued images[J]. Journal of Visual Communication and Image Representation, 2000, 11(2): 130-141.
[5] Tuceryan M. Moment-based texture segmentation [J]. Pattern Recognition Letters, 1994, 15(7): 659-668.
[6] 李海啸, 姜璐, 舒华忠. 基于Zernike矩和BP神经网络的纹理分割[J]. 东南大学学报: 自然科学版, 2005, 35(2): 199-201.
  Li Haixiao, Jiang Lu, Shu Huazhong. Texture segmentation based on Zernike moment and BP neural network[J]. Journal of Southeast University:Natural Science Edition, 2005, 35(2): 199-201.(in Chinese)
[7] Chen Z, Sun S K. A Zernike moment phase-based descriptor for local image representation and matching [J]. IEEE Transactions on Image Processing, 2010, 19(1): 205-219.
[8] Sintorn I M, Kylberg G. Regional Zernike moments for texture recognition[C]//IEEE 21st International Conference on Pattern Recognition. Tsukuba, Japan, 2012: 1635-1638.
[9] Ryu S J, Kirchner M, Lee M J, et al. Rotation invariant localization of duplicated image regions based on Zernike moments[J]. IEEE Transactions on Information Forensics and Security, 2013, 8(8): 1355-1370.
[10] 吴柯. 基于矩的纹理分割及其在超声图像中的应用[D]. 南京:东南大学生物科学与医学工程学院, 2009.

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备注/Memo

备注/Memo:
收稿日期: 2014-12-29.
作者简介: 郭骁(1990—),男,硕士生;舒华忠(联系人),男,博士,教授,博士生导师,shu.list@seu.edu.cn.
基金项目: 国家重点基础研究发展计划(973计划)资助项目(2011CB707904)、国家自然科学基金资助项目(61073138,61103141,61271312,61201344).
引用本文: 郭骁,杨冠羽,王征,等.基于Zernike矩和水平集的超声图像分割[J].东南大学学报:自然科学版,2015,45(2):247-250. [doi:10.3969/j.issn.1001-0505.2015.02.009]
更新日期/Last Update: 2015-03-20