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Geometrical Regularization of Displacement Fields with Application to Biological Image Registration

机译:位移场的几何正则化及其在生物图像配准中的应用

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This article tackles the registration of 2-D biological images (histological sections, autoradiographs, cryosections, etc.). The large variety of registration applications - 3D volume reconstruction, cross-dye histology gene mapping, etc. - induce an equally diverse set of requirements in terms of accuracy and robustness. In turn, these directly translate into regularization constraints on the deformation model, which should ideally be specifiable in a user-friendly fashion. We propose an adaptive regularization approach where the rigidity constraints are informed by the registration application at hand and whose support is controlled by the geometry of the images to be registered. We investigate the behavior of this technique and discuss its sensitivity to the rigidity parameter.
机译:本文介绍了二维生物图像(组织切片,放射自显影照片,冷冻切片等)的注册问题。各种各样的配准应用程序-3D体积重建,跨染料组织学基因定位等-在准确性和鲁棒性方面引起了同样多样化的要求。反过来,这些直接转化为变形模型的正则约束,理想情况下应以用户友好的方式指定。我们提出一种自适应正则化方法,其中刚度约束由手边的配准应用程序通知,并且其支持由要配准的图像的几何形状控制。我们调查此技术的行为,并讨论其对刚度参数的敏感性。

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