IEEE Trans Med Imaging. 2019 Jun;38(6):1488-1500. doi: 10.1109/TMI.2019.2896170. Epub 2019 Jan 31.
Deformable image registration is a widely used technique in the field of computer vision and medical image processing. Basically, the task of deformable image registration is to find the displacement field between the moving image and the fixed image. Many variational models are proposed for deformable image registration, under the assumption that the displacement field is continuous and smooth. However, displacement fields may be discontinuous, especially for medical images with intensity inhomogeneity, pathological tissues, or heavy noises. In the mathematical theory of elastoplasticity, when the displacement fields are possibly discontinuous, a suitable framework for describing the displacement fields is the space of functions of bounded deformation (BD). Inspired by this, we propose a novel deformable registration model, called the BD model, which allows discontinuities of displacement fields in images. The BD model is formulated in a variational framework by supposing the displacement field to be a function of BD. The existence of solutions of this model is proven. Numerical experiments on 2D images show that the BD model outperforms the classical demons model, the log-domain diffeomorphic demons model, and the state-of-the-art vectorial total variation model. Numerical experiments on two public 3D databases show that the target registration error of the BD model is competitive compared with more than ten other models.
可变形图像配准是计算机视觉和医学图像处理领域中广泛使用的技术。基本上,可变形图像配准的任务是找到运动图像和固定图像之间的位移场。许多变分模型被提出用于可变形图像配准,假设位移场是连续和光滑的。然而,位移场可能是不连续的,特别是对于具有强度不均匀性、病理组织或严重噪声的医学图像。在弹塑性力学的数学理论中,当位移场可能不连续时,描述位移场的合适框架是有界变形函数的空间 (BD)。受此启发,我们提出了一种新的可变形配准模型,称为 BD 模型,它允许图像中的位移场存在不连续性。该模型通过假设位移场是 BD 函数在变分框架中进行了公式化。证明了该模型解的存在性。二维图像的数值实验表明,BD 模型优于经典的 demons 模型、对数域仿射 demons 模型和最先进的矢量全变分模型。两个公共的 3D 数据库的数值实验表明,与其他十多个模型相比,BD 模型的目标配准误差具有竞争力。