TILT CORRECTION METHODS FOR CT AND MR MEDICAL IMAGES

Abstract

In this paper, the tilt correction of computerized tomography (CT) and magnetic resonance (MR) medical images is the main point of interest. The centroid of the medical subimage is calculated, and the rotation angle α is obtained by separately using two methods: singular value decomposition (SVD) and principal component analysis (PCA), respectively. In addition, the whole medical image is rotated around the centroid by -α to correct the tilt. Based on this, according to the uniformity of the medical subimage the rotation angle α is further adjusted, which achieves better correction effect and performance. The experimental results show that the correction effect of SVD is the same as that of PCA, the proposed methods are fairly reliable and accurate for the determination of tilt angles, and are practical and effective tilt correction techniques. In addition, the correction methods are regarded as the preprocesses of image registration, and hence are used to get the registering parameters by incorporating the pattern search method. The experimental results reveal that they can significantly reduce the computational load, accurately get transformation parameters, and overcome the problem of easily getting into the local optimum.