Non-rigid consistent registration of 2D image sequences
Non-rigid consistent registration of 2D image sequences
复制标题
二维图像序列的非刚性一致配准
DOI：
10.1088/0031-9155/55/20/012
复制
发表时间：
2010-10-21
影响因子：
3.5
通讯作者：
Ortiz-de Solorzano, C.
中科院分区：
文献类型：
--
作者：
Arganda-Carreras, I.;Sorzano, C. O. S.;Ortiz-de Solorzano, C.
结合多分辨率b样条弹性配准和双向一致配准的原理，提出了一种新的二维图像序列配准算法。在我们的方法中，连续的图像三元组迭代配准，通过整个序列的图像集逐步扩展信息。中间结果将用于注册以下三元组。我们选择插值图像，并使用b样条多分辨率金字塔对变形场进行建模。为了更好地描述边界处的变形，引入了新的边界条件。在实验部分，我们定量地证明了我们的方法可以从桶/针垫和鱼眼变形中恢复，具有亚像素误差。此外，它比最先进的方法更能抵抗异常值——偶尔的强噪声和大旋转。最后，我们证明我们的方法可以用来重新排列一系列的组织学序列切片，这些切片通常由于组织的折叠和撕裂而严重扭曲。
We present a novel algorithm for the registration of 2D image sequences that combines the principles of multiresolution B-spline-based elastic registration and those of bidirectional consistent registration. In our method, consecutive triples of images are iteratively registered to gradually extend the information through the set of images of the entire sequence. The intermediate results are reused for the registration of the following triple. We choose to interpolate the images and model the deformation fields using B-spline multiresolution pyramids. Novel boundary conditions are introduced to better characterize the deformations at the boundaries. In the experimental section, we quantitatively show that our method recovers from barrel/pincushion and fish-eye deformations with subpixel error. Moreover, it is more robust against outliers-occasional strong noise and large rotations-than the state-of-the-art methods. Finally, we show that our method can be used to realign series of histological serial sections, which are often heavily distorted due to folding and tearing of the tissues.