MEDICAL IMAGE REGISTRATION BASED ON IMPROVED FUZZY C-MEANS CLUSTERING

被引:5
作者
Pan, Meisen [1 ]
Jiang, Jianjun [1 ]
Zhang, Fen [1 ]
Rong, Qiusheng [1 ]
机构
[1] Hunan Univ Arts & Sci, Coll Comp Sci & Technol, Changde 415000, Peoples R China
来源
BIOMEDICAL ENGINEERING-APPLICATIONS BASIS COMMUNICATIONS | 2015年 / 27卷 / 04期
基金
中国国家自然科学基金;
关键词
Image registration; Fuzzy C-means clustering; Iterative closest points; Mutual information;
D O I
10.4015/S1016237215500325
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
The mutual information (MI) technology and the iterative closest point (ICP) algorithm, as intensity-based and feature-based image registration methods respectively, are commonly put into use in medical image registration. But some naturally existing things which restrict the further development need to be faced and be solved. On one hand, they remain heavy calculation costs and low registration efficiencies. On the other hand, since they seriously depend on whether the initial rotation and translation registration parameters can be exactly selected, they often trap in the local optima and even fail to register images. In this paper, we compute the centroids of the reference and floating images by using the image moments to obtain the initial translation values, and use improved fuzzy C-means clustering (IFCM) to classify the image coordinates. Before clustering, this proposed method first centralizes the medical image coordinates, creates the two-row coordinate matrix to construct the two-dimensional (2D) sample set partitioned into two classes, and computes the slope of a straight line fitted to the two classes, finally derives the rotation angle from solving the arc tangent of the slope and obtains the initial rotation values. The experimental results show that, this proposed method has a fairly simple implementation, a low computational load, a fast registration and good registration accuracy. Also, it can efficiently avoid trapping in the local optima and meets both mono-modality and multi-modality image registrations.
引用
收藏
页数:11
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