仿射变换
转化(遗传学)
计算机科学
计算机视觉
线性地图
相似性(几何)
矩阵相似性
人工智能
变形(气象学)
图像配准
点(几何)
图像(数学)
算法
集合(抽象数据类型)
航程(航空)
地标
坐标系
数学
几何学
数学分析
纯数学
物理
生物化学
化学
气象学
基因
材料科学
复合材料
偏微分方程
程序设计语言
作者
Pilar Castellanos,Pedro Luis del Angel,V. Medina
摘要
A fully automatic method to deform medical images is proposed. The procedure is based on the application of a set of consecutive local linear transformations at fixed landmarks, generating a global non-linear deformation. Continuity is guaranteed by a smooth change form the landmark point to the neighborhood, which is a homotopy between an affine transformation and the identity map. Landmarks are distributed uniformly throughout both reference and target images and their density is increased to reach the desired similarity between both images. A hybrid genetic optimization algorithm is used to search for the transformation parameters by maximizing the normalized mutual information. It is shown, by means of the transformation of a circle into a triangle and vice versa, that the method has the capability to generate either sharp of smooth deformations. For magnetic resonance images, it is proved that the successive application of the local linear transformations allows us to increase the similarity between geometrically deformed images and target. The results suggest that the method can be applied to a wide range of non-rigid image registration problems.
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