Real-time multi-modal rigid registration based on a novel symmetric-SIFT descriptor
文献类型：期刊论文
| 作者 | Chen, Jian ; Tian, Jie
|
| 刊名 | PROGRESS IN NATURAL SCIENCE
 |
| 出版日期 | 2009-05-10 |
| 卷号 | 19期号:5页码:643-651 |
| 关键词 | Symmetric-SIFT Multi-modal Registration Keypoint Matching |
| 英文摘要 | The purpose of image registration is to spatially align two or more single-modality images taken at different times, or several images acquired by multiple imaging modalities. Intensity-based registration usually requires optimization of the similarity metric between the images. However, global optimization techniques are too time-consuming, and local optimization techniques frequently fail to search the global transformation space because of the large initial misalignment of the two images. Moreover, for large non-overlapping area registration, the similarity metric cannot reach its optimum value when the two images are properly registered. In order to solve these problems, we propose a novel Symmetric Scale Invariant Feature Transform (symmetric-SIFT) descriptor and develop a fast multi-modal image registration technique. The proposed technique automatically generates a lot of highly distinctive symmetric-SIFT descriptors for two images, and the registration is performed by matching the corresponding descriptors over two images. These descriptors are invariant to image scale and rotation, and are partially invariant to affine transformation. Moreover, these descriptors are symmetric to contrast, which makes it suitable for multi-modal image registration. The proposed technique abandons the optimization and similarity metric strategy. It works with near real-time performance, and can deal with the large non-overlapping and large initial misalignment situations. Test cases involving scale change, large non-overlapping, and large initial misalignment on computed tomography (CT) and magnetic resonance (MR) datasets show that it needs much less runtime and achieves better accuracy when compared to other algorithms. (C) 2009 National Natural Science Foundation of China and Chinese Academy of Sciences. Published by Elsevier Limited and Science in China Press. All rights reserved. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Materials Science, Multidisciplinary ; Multidisciplinary Sciences |
| 研究领域[WOS] | Materials Science ; Science & Technology - Other Topics |
| 关键词[WOS] | IMAGE REGISTRATION ; MUTUAL-INFORMATION ; OPTIMIZATION ; ALIGNMENT |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000264659800015 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/3969]  |
| 专题 | 自动化研究所_中国科学院分子影像重点实验室 |
| 作者单位 | Chinese Acad Sci, Inst Automat, Beijing 100080, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Jian,Tian, Jie. Real-time multi-modal rigid registration based on a novel symmetric-SIFT descriptor[J]. PROGRESS IN NATURAL SCIENCE,2009,19(5):643-651. |
| APA | Chen, Jian,&Tian, Jie.(2009).Real-time multi-modal rigid registration based on a novel symmetric-SIFT descriptor.PROGRESS IN NATURAL SCIENCE,19(5),643-651. |
| MLA | Chen, Jian,et al."Real-time multi-modal rigid registration based on a novel symmetric-SIFT descriptor".PROGRESS IN NATURAL SCIENCE 19.5(2009):643-651. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。