Multi-modality liver image registration based on multilevel B-splines free-form deformation and L-BFGS optimal algorithm

作     者：宋红 李佳佳 王树良 马婧婷 SONG Hong;LI Jia-jia;WANG Shu-liang;MA Jing-ting

作者机构：School of SoftwareBeijing Institute of Technology School of Computer ScienceBeijing Institute of Technology 

出 版 物：《Journal of Central South University》 (中南大学学报（英文版）)

年 卷 期：2014年第21卷第1期

页      面：287-292页

核心收录：

学科分类：07[理学] 08[工学] 080203[工学-机械设计及理论] 070102[理学-计算数学] 0802[工学-机械工程] 0701[理学-数学] 

基　　金：Project(61240010)supported by the National Natural Science Foundation of China Project(20070007070)supported by Specialized Research Fund for the Doctoral Program of Higher Education of China 

主　　题：multi-modal image registration affine transformation B-splines free-form deformation (FFD) L-BFGS 

摘      要：A new coarse-to-fine strategy was proposed for nonrigid registration of computed tomography(CT) and magnetic resonance(MR) images of a *** hierarchical framework consisted of an affine transformation and a B-splines free-form deformation(FFD).The affine transformation performed a rough registration targeting the mismatch between the CT and MR *** B-splines FFD transformation performed a finer registration by correcting local motion *** the registration algorithm,the normalized mutual information(NMI) was used as similarity measure,and the limited memory Broyden-Fletcher- Goldfarb-Shannon(L-BFGS) optimization method was applied for optimization *** algorithm was applied to the fully automated registration of liver CT and MR images in three *** results demonstrate that the proposed method not only significantly improves the registration accuracy but also reduces the running time,which is effective and efficient for nonrigid registration.