@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}
}