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Volume 7, Issue 3
A Fast Rigid Registration Algorithm for Medical Images

Yuncong Feng, Xiongfei Li, Xiaoli Zhang & Tienan Ding

Journal of Fiber Bioengineering & Informatics, 7 (2014), pp. 409-418.

Published online: 2014-07

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  • Abstract
Image registration is a vital research branch in medical image processing and analysis. In this paper, we proposed a new framework for rigid medical image registration. It can also be regarded as a pre-processing of non-rigid image registration algorithms. The interest of the algorithm lies in its simplicity and high effciency. In the registration algorithm, we firstly segmented the reference image and float image into two parts: tissue parts and background parts. Then the centers of the two images were located through performing distance transform on the two segmented tissue images. Finally, we detected the longest radius of the two tissue regions, by which we determined the rotating angle. We tested the registration algorithm on dozens of medical images, and the experimental results show us that the algorithm is competent for medical image registration.
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@Article{JFBI-7-409, author = {Yuncong Feng, Xiongfei Li, Xiaoli Zhang and Tienan Ding }, title = {A Fast Rigid Registration Algorithm for Medical Images}, journal = {Journal of Fiber Bioengineering and Informatics}, year = {2014}, volume = {7}, number = {3}, pages = {409--418}, abstract = {Image registration is a vital research branch in medical image processing and analysis. In this paper, we proposed a new framework for rigid medical image registration. It can also be regarded as a pre-processing of non-rigid image registration algorithms. The interest of the algorithm lies in its simplicity and high effciency. In the registration algorithm, we firstly segmented the reference image and float image into two parts: tissue parts and background parts. Then the centers of the two images were located through performing distance transform on the two segmented tissue images. Finally, we detected the longest radius of the two tissue regions, by which we determined the rotating angle. We tested the registration algorithm on dozens of medical images, and the experimental results show us that the algorithm is competent for medical image registration.}, issn = {2617-8699}, doi = {https://doi.org/10.3993/jfbi09201410}, url = {http://global-sci.org/intro/article_detail/jfbi/4796.html} }
TY - JOUR T1 - A Fast Rigid Registration Algorithm for Medical Images AU - Yuncong Feng, Xiongfei Li, Xiaoli Zhang & Tienan Ding JO - Journal of Fiber Bioengineering and Informatics VL - 3 SP - 409 EP - 418 PY - 2014 DA - 2014/07 SN - 7 DO - http://doi.org/10.3993/jfbi09201410 UR - https://global-sci.org/intro/article_detail/jfbi/4796.html KW - Image Registration KW - Medical Image KW - Image Segment KW - Distance Transformation AB - Image registration is a vital research branch in medical image processing and analysis. In this paper, we proposed a new framework for rigid medical image registration. It can also be regarded as a pre-processing of non-rigid image registration algorithms. The interest of the algorithm lies in its simplicity and high effciency. In the registration algorithm, we firstly segmented the reference image and float image into two parts: tissue parts and background parts. Then the centers of the two images were located through performing distance transform on the two segmented tissue images. Finally, we detected the longest radius of the two tissue regions, by which we determined the rotating angle. We tested the registration algorithm on dozens of medical images, and the experimental results show us that the algorithm is competent for medical image registration.
Yuncong Feng, Xiongfei Li, Xiaoli Zhang and Tienan Ding . (2014). A Fast Rigid Registration Algorithm for Medical Images. Journal of Fiber Bioengineering and Informatics. 7 (3). 409-418. doi:10.3993/jfbi09201410
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