Auer Martin, Regitnig Peter, Holzapfel Gerhard A
Institute for Structural Analysis, Computational Biomechanics, Graz University of Technology, A-8010 Graz, Austria.
IEEE Trans Image Process. 2005 Apr;14(4):475-86. doi: 10.1109/tip.2005.843756.
Automatic computer-based analyses of histological sections which are differently stained require that they are related to each other. Most registration methods are only able to perform rigid-body motion and are sensitive to noise and artifacts. Histological images, however, are accompanied by several artifacts and different contrasts, which require a nonrigid registration. In this paper, we present a hierarchical nonrigid registration algorithm able to align images, which contain minor image artifacts. The algorithm requires no a priori knowledge of the true image. The hierarchical design of the algorithm enhances robustness and accuracy, and saves computational costs. The proposed algorithm is decomposed into a fast, coarse, rigid registration step and a slower, but finer, nonrigid step. For the coarse registration, we use image pyramids, while for the second step, we combine a point-based registration with an elastic thin-plate spline interpolation. Accuracy tests, performed for 20 histological images obtained from human arteries, have shown that the error measure is acceptable, and that the image noise does not cause a problem. The associated convergence rate of the mean pixel displacement error during the rigid and nonrigid registrations is satisfying. The algorithm can be applied to various multicontrast elastic registration problems in medical imaging and may be extended to three dimensions.
对不同染色的组织切片进行基于计算机的自动分析,需要将它们相互关联起来。大多数配准方法仅能执行刚体运动,并且对噪声和伪影敏感。然而,组织学图像伴随着多种伪影和不同的对比度,这就需要非刚体配准。在本文中,我们提出了一种分层非刚体配准算法,能够对齐包含少量图像伪影的图像。该算法不需要真实图像的先验知识。算法的分层设计提高了鲁棒性和准确性,并节省了计算成本。所提出的算法被分解为一个快速、粗略的刚体配准步骤和一个较慢但更精细的非刚体步骤。对于粗略配准,我们使用图像金字塔,而对于第二步,我们将基于点的配准与弹性薄板样条插值相结合。对从人体动脉获得的20幅组织学图像进行的准确性测试表明,误差度量是可接受的,并且图像噪声不会造成问题。在刚体和非刚体配准过程中,平均像素位移误差的相关收敛速度令人满意。该算法可应用于医学成像中的各种多对比度弹性配准问题,并可扩展到三维。