CASIA OpenIR  > 中国科学院分子影像重点实验室
Fast Rotation-Free Feature-Based Image Registration Using Improved N-SIFT and GMM-Based Parallel Optimization
Yu, Dongdong1; Yang, Feng2; Yang, Caiyun1; Leng, Chengcai3; Cao, Jian4,5; Wang, Yining4,5; Tian, Jie1
发表期刊IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
2016-08-01
卷号63期号:8页码:1653-1664
文章类型Article
摘要Image registration is a key problem in a variety of applications, such as computer vision, medical image processing, pattern recognition, etc., while the application of registration is limited by time consumption and the accuracy in the case of large pose differences. Aimed at these two kinds of problems, we propose a fast rotation-free feature-based rigid registration method based on our proposed accelerated-NSIFT and GMM registration based parallel optimization (PO-GMMREG). Our method is accelerated by using the GPU/CUDA programming and preserving only the location information without constructing the descriptor of each interest point, while its robustness to missing correspondences and outliers is improved by converting the interest point matching to Gaussian mixture model alignment. The accuracy in the case of large pose differences is settled by our proposed PO-GMMREG algorithm by constructing a set of initial transformations. Experimental results demonstrate that our proposed algorithm can fast rigidly register 3-D medical images and is reliable for aligning 3-D scans even when they exhibit a poor initialization.
关键词Accelerated Nsift Medical Imaging Parallel OptimizatiOn Based On Gaussian Mixture Model Rigid Image Registration Rotation-free
WOS标题词Science & Technology ; Technology
DOI10.1109/TBME.2015.2465855
关键词[WOS]ALGORITHM ; ACCURACY
收录类别SCI
语种英语
项目资助者National Basic Research Program of China (973 Program)(2011CB707700) ; National Natural Science Foundation of China(81227901 ; Chinese Academy of Sciences(2013Y1GB0005) ; National High Technology Research and Development Program of China (863 Program)(2012AA021105) ; Guangdong Province-Chinese Academy of Sciences(2010A090100032 ; NSFC-NIH(81261120414) ; Beijing Natural Science Foundation(4132080) ; Fundamental Research Funds for the Central Universities(2013JBZ014) ; National Basic Research Program of China(61301002) ; State Key Laboratory of Management and Control for Complex Systems(20140101) ; 61231004 ; 2012B090400039) ; 61363049)
WOS研究方向Engineering
WOS类目Engineering, Biomedical
WOS记录号WOS:000380325000010
引用统计
被引频次:25[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/12171
专题中国科学院分子影像重点实验室
通讯作者Tian, Jie
作者单位1.Chinese Acad Sci, Key Lab Mol Imaging, Inst Automat, Beijing 100190, Peoples R China
2.Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing, Peoples R China
3.Nanchang Hangkong Univ, Sch Math & Informat Sci, Nanchang, Peoples R China
4.Chinese Acad Med Sci, Peking Union Med Coll Hosp, Dept Radiol, Beijing, Peoples R China
5.Peking Union Med Coll, Beijing, Peoples R China
推荐引用方式
GB/T 7714
Yu, Dongdong,Yang, Feng,Yang, Caiyun,et al. Fast Rotation-Free Feature-Based Image Registration Using Improved N-SIFT and GMM-Based Parallel Optimization[J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING,2016,63(8):1653-1664.
APA Yu, Dongdong.,Yang, Feng.,Yang, Caiyun.,Leng, Chengcai.,Cao, Jian.,...&Tian, Jie.(2016).Fast Rotation-Free Feature-Based Image Registration Using Improved N-SIFT and GMM-Based Parallel Optimization.IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING,63(8),1653-1664.
MLA Yu, Dongdong,et al."Fast Rotation-Free Feature-Based Image Registration Using Improved N-SIFT and GMM-Based Parallel Optimization".IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 63.8(2016):1653-1664.
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