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一种使用大规模约束优化对雅可比矩阵施加约束的快速非刚性图像配准方法。

A fast nonrigid image registration with constraints on the Jacobian using large scale constrained optimization.

作者信息

Sdika Michaël

机构信息

AIMS Group, Department of Neurology, University of California, San Francisco, San Francisco, CA 94107, USA.

出版信息

IEEE Trans Med Imaging. 2008 Feb;27(2):271-81. doi: 10.1109/TMI.2007.905820.

Abstract

This paper presents a new nonrigid monomodality image registration algorithm based on B-splines. The deformation is described by a cubic B-spline field and found by minimizing the energy between a reference image and a deformed version of a floating image. To penalize noninvertible transformation, we propose two different constraints on the Jacobian of the transformation and its derivatives. The problem is modeled by an inequality constrained optimization problem which is efficiently solved by a combination of the multipliers method and the L-BFGS algorithm to handle the large number of variables and constraints of the registration of 3-D images. Numerical experiments are presented on magnetic resonance images using synthetic deformations and atlas based segmentation.

摘要

本文提出了一种基于B样条的新型非刚性单模态图像配准算法。变形由三次B样条场描述,并通过最小化参考图像与浮动图像变形版本之间的能量来找到。为了惩罚不可逆变换,我们对变换的雅可比矩阵及其导数提出了两种不同的约束。该问题被建模为一个不等式约束优化问题,通过乘子法和L-BFGS算法的组合有效地求解,以处理三维图像配准中大量的变量和约束。使用合成变形和基于图谱的分割对磁共振图像进行了数值实验。

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