Year: 2015
Journal of Fiber Bioengineering and Informatics, Vol. 8 (2015), Iss. 1 : pp. 151–159
Abstract
This proposed method calculates the centroids of two registering images by applying the moments for acquiring the original displacement parameters, and then uses modified K-means clustering to classify the image coordinates. Before clustering, the medical image coordinates is centralized, the two-row coordinate matrix is created to construct the 2-D sample set to be partitioned into two classes, the slope of a straight line fitted to the two classes is computed, and the rotation angle is computed by solving the arc tangent of the slope. The edges are detected by the edge convolution kernel and the binary images covering the characteristic points are extracted. Experimental results from aligning experiments reveal that, this approach has lower computation costs and a higher registration precision.
You do not have full access to this article.
Already a Subscriber? Sign in as an individual or via your institution
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.3993/jfbi03201515
Journal of Fiber Bioengineering and Informatics, Vol. 8 (2015), Iss. 1 : pp. 151–159
Published online: 2015-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 9
Keywords: Centroids