用拉东变换提升噪声下非仿射图像配准精度
Methods based on Radon transform for non-affine deformable image registration of noisy images
- 基于拉东变换构建相似性度量，捕捉复杂非仿射形变
- 在含噪与无噪图像上均实现稳定配准，收敛性良好
- 适用于肺部等医学图像配准，对噪声鲁棒性强
可变形图像配准是通过比较物体不同状态下的两幅图像来确定其形变的标准工程问题。本文提出两种新方法，利用基于拉东变换的相似性度量和基于线弹性形变能量的经典正则化项，以捕捉非仿射形变。研究建立了两种方法解的存在性与唯一性条件，并通过合成实验对比了标准的平方差和相似性度量方法。所提方法在含噪与无噪图像上均成功捕捉多种非仿射形变，分析了收敛速率。此外，在肺部图像配准场景中验证了其有效性。
原文摘要 · Abstract (English)
Deformable image registration is a standard engineering problem used to determine the distortion experienced by a body by comparing two images of it in different states. This study introduces two new DIR methods designed to capture non-affine deformations using Radon transform-based similarity measures and a classical regularizer based on linear elastic deformation energy. It establishes conditions for the existence and uniqueness of solutions for both methods and presents synthetic experimental results comparing them with a standard method based on the sum of squared differences similarity measure. These methods have been tested to capture various non-affine deformations in images, both with and without noise, and their convergence rates have been analyzed. Furthermore, the effectiveness of these methods was also evaluated in a lung image registration scenario.
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