Multimodal Image Alignment via Linear Mapping between Feature Modalities

We propose a novel landmark matching based method for aligning multimodal images, which is accomplished uniquely by resolving a linear mapping between different feature modalities. This linear mapping results in a new measurement on similarity of images captured from different modalities. In additio...

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Main Authors:	Yanyun Jiang, Yuanjie Zheng, Sujuan Hou, Yuchou Chang, James Gee
Format:	Article
Language:	English
Published:	Hindawi Limited 2017-01-01
Series:	Journal of Healthcare Engineering
Online Access:	http://dx.doi.org/10.1155/2017/8625951

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spelling	doaj-ed4a904e14464a4d80dd5948a854e9332020-11-24T21:55:37ZengHindawi LimitedJournal of Healthcare Engineering2040-22952040-23092017-01-01201710.1155/2017/86259518625951Multimodal Image Alignment via Linear Mapping between Feature ModalitiesYanyun Jiang0Yuanjie Zheng1Sujuan Hou2Yuchou Chang3James Gee4School of Information Science and Engineering, Key Lab of Intelligent Computing & Information Security in Universities of Shandong, Institute of Life Sciences, Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology and Key Lab of Intelligent Information Processing, Shandong Normal University, Jinan, Shandong 250014, ChinaSchool of Information Science and Engineering, Key Lab of Intelligent Computing & Information Security in Universities of Shandong, Institute of Life Sciences, Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology and Key Lab of Intelligent Information Processing, Shandong Normal University, Jinan, Shandong 250014, ChinaSchool of Information Science and Engineering, Key Lab of Intelligent Computing & Information Security in Universities of Shandong, Institute of Life Sciences, Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology and Key Lab of Intelligent Information Processing, Shandong Normal University, Jinan, Shandong 250014, ChinaComputer Science and Engineering Technology Department, University of Houston-Downtown, Houston, TX 77002, USAPerelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USAWe propose a novel landmark matching based method for aligning multimodal images, which is accomplished uniquely by resolving a linear mapping between different feature modalities. This linear mapping results in a new measurement on similarity of images captured from different modalities. In addition, our method simultaneously solves this linear mapping and the landmark correspondences by minimizing a convex quadratic function. Our method can estimate complex image relationship between different modalities and nonlinear nonrigid spatial transformations even in the presence of heavy noise, as shown in our experiments carried out by using a variety of image modalities.http://dx.doi.org/10.1155/2017/8625951
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Yanyun Jiang Yuanjie Zheng Sujuan Hou Yuchou Chang James Gee
spellingShingle	Yanyun Jiang Yuanjie Zheng Sujuan Hou Yuchou Chang James Gee Multimodal Image Alignment via Linear Mapping between Feature Modalities Journal of Healthcare Engineering
author_facet	Yanyun Jiang Yuanjie Zheng Sujuan Hou Yuchou Chang James Gee
author_sort	Yanyun Jiang
title	Multimodal Image Alignment via Linear Mapping between Feature Modalities
title_short	Multimodal Image Alignment via Linear Mapping between Feature Modalities
title_full	Multimodal Image Alignment via Linear Mapping between Feature Modalities
title_fullStr	Multimodal Image Alignment via Linear Mapping between Feature Modalities
title_full_unstemmed	Multimodal Image Alignment via Linear Mapping between Feature Modalities
title_sort	multimodal image alignment via linear mapping between feature modalities
publisher	Hindawi Limited
series	Journal of Healthcare Engineering
issn	2040-2295 2040-2309
publishDate	2017-01-01
description	We propose a novel landmark matching based method for aligning multimodal images, which is accomplished uniquely by resolving a linear mapping between different feature modalities. This linear mapping results in a new measurement on similarity of images captured from different modalities. In addition, our method simultaneously solves this linear mapping and the landmark correspondences by minimizing a convex quadratic function. Our method can estimate complex image relationship between different modalities and nonlinear nonrigid spatial transformations even in the presence of heavy noise, as shown in our experiments carried out by using a variety of image modalities.
url	http://dx.doi.org/10.1155/2017/8625951
work_keys_str_mv	AT yanyunjiang multimodalimagealignmentvialinearmappingbetweenfeaturemodalities AT yuanjiezheng multimodalimagealignmentvialinearmappingbetweenfeaturemodalities AT sujuanhou multimodalimagealignmentvialinearmappingbetweenfeaturemodalities AT yuchouchang multimodalimagealignmentvialinearmappingbetweenfeaturemodalities AT jamesgee multimodalimagealignmentvialinearmappingbetweenfeaturemodalities
_version_	1725861474664972288

Multimodal Image Alignment via Linear Mapping between Feature Modalities

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