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基于强度的对比增强乳腺磁共振图像的容积配准

Intensity-based volumetric registration of contrast-enhanced MR breast images.

作者信息

Sun Yin, Yan Chye Hwang, Ong Sim-Heng, Tan Ek Tsoon, Wang Shih-Chang

机构信息

Department of Electrical and Computer Engineering, National University of Singapore.

出版信息

Med Image Comput Comput Assist Interv. 2006;9(Pt 1):671-8. doi: 10.1007/11866565_82.

Abstract

In this paper, we propose a fast intensity-based registration algorithm for the analysis of contrast-enhanced breast MR images. Motion between pre-contrast and post-contrast images has been modeled by a combination of rigid transformation and free-form deformation. By modeling the conditional probability function to be Gaussian and considering the normalized mutual information (NMI) criterion, we create a pair of auxiliary images to speed up the registration process. The auxiliary images are registered to the actual images by optimizing the simple sum of squared difference (SSD) criterion. The overall registration is achieved by linearly combining the deformation observed in the auxiliary images. One well-known problem of non-rigid registration of contrast enhanced images is the contraction of enhanced lesion volume. We address this problem by rejecting the intensity outliers from registration. Results have shown that our method could achieve accurate registration of the data while successfully prevent the contraction of the contrast enhanced lesion volume.

摘要

在本文中,我们提出了一种基于强度的快速配准算法,用于分析对比增强乳腺磁共振图像。通过结合刚体变换和自由形式变形对造影前和造影后图像之间的运动进行建模。通过将条件概率函数建模为高斯分布并考虑归一化互信息(NMI)准则,我们创建了一对辅助图像以加速配准过程。通过优化简单平方差(SSD)准则将辅助图像配准到实际图像。通过线性组合在辅助图像中观察到的变形来实现整体配准。对比增强图像非刚性配准的一个众所周知的问题是增强病变体积的收缩。我们通过在配准中剔除强度异常值来解决这个问题。结果表明,我们的方法可以实现数据的精确配准,同时成功防止对比增强病变体积的收缩。

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