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基于互信息的颞侧和立体视网膜图像约束优化配准

Mutual information-based registration of temporal and stereo retinal images using constrained optimization.

作者信息

Zhu Yang-Ming

出版信息

Comput Methods Programs Biomed. 2007 Jun;86(3):210-5. doi: 10.1016/j.cmpb.2007.02.007. Epub 2007 Apr 16.

DOI:10.1016/j.cmpb.2007.02.007
PMID:17434643
Abstract

In the registration of temporal and stereo retinal images, the rotation angle is normally less than 5 degrees and the scaling factor is between 0.95 and 1.05. Due to sitting constraints in the imaging process, the x translation can be more than 100 pixels, but the y translation is usually small. This paper successfully incorporates these constraints in the mutual information-based registration and exploits a constrained optimization to seek an optimal registration. The proposed approach increases the success rate of the registration algorithm significantly. The impacts of the dynamic ranges of registration parameters on the registration outcome are studied and the effects of the order of rotation, scaling, and translation are also investigated.

摘要

在颞侧和立体视网膜图像配准中,旋转角度通常小于5度,缩放因子在0.95至1.05之间。由于成像过程中的坐姿限制,x轴平移可能超过100像素,但y轴平移通常较小。本文成功地将这些约束纳入基于互信息的配准中,并利用约束优化来寻求最优配准。所提出的方法显著提高了配准算法的成功率。研究了配准参数动态范围对配准结果的影响,并研究了旋转、缩放和平移顺序的影响。

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