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二维图像序列的非刚性一致配准。

Non-rigid consistent registration of 2D image sequences.

机构信息

Biocomputing Unit, National Centre for Biotechnology, CSIC, Darwin 3, Universidad Autónoma de Madrid, 28049 Madrid, Spain.

出版信息

Phys Med Biol. 2010 Oct 21;55(20):6215-42. doi: 10.1088/0031-9155/55/20/012. Epub 2010 Sep 30.

Abstract

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.

摘要

我们提出了一种新的算法,用于注册 2D 图像序列,该算法结合了多分辨率 B 样条弹性配准和双向一致配准的原理。在我们的方法中,连续的三幅图像被迭代注册,以逐渐通过整个序列的图像集扩展信息。中间结果被重新用于注册下一个三幅图像。我们选择使用 B 样条多分辨率金字塔来插值图像并建模变形场。引入了新的边界条件来更好地描述边界处的变形。在实验部分,我们定量地表明,我们的方法可以以亚像素的误差从桶形/枕形和鱼眼变形中恢复。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,我们表明我们的方法可以用于重新排列组织学系列切片,由于组织的折叠和撕裂,这些切片通常会严重变形。

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