TY - JOUR
T1 - A New Medical Image Registration
JO - Journal of Fiber Bioengineering and Informatics
VL - 1
SP - 151
EP - 159
PY - 2015
DA - 2015/08
SN - 8
DO - http://doi.org/10.3993/jfbi03201515
UR - https://global-sci.org/intro/article_detail/jfbi/4695.html
KW - Centroids
KW - Image Registration
KW - K-means Clustering
KW - Iterative Closest Points
AB - 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.