Optimal registration method based on ICP algorithm from head CT and MR image sets

Abstract

Image registration is an important problem and a fundamental task for understanding the internal organ or internal structure of human body, analyzing the temporal change from the image sets which is obtained different time series in computer vision and image processing field. Especially, CT and MR imaging of the head for diagnosis and surgical planning indicate that physicians and surgeons gain important information from these modalities. In radiotherapy planning, manual registration techniques are performed on MR and CT images of the brain. In general, physicians segment the volumes of interest (VOIs) from each set of slices on the MR and CT images manually. However, manual registration of the object area may require several hours for analysis based on anatomical knowledge. In this paper, to register two images which are obtained from different modalities we develop a new method for automatic registration of the head CT and MR images by using ICP (iterative closest point) algorithm in several extracted data and maximization of mutual information. One of the benefits of using the ICP algorithm is that computational costs can be reduced on the registration. The primary objective of this study is to increase the registration accuracy and reduce the computational processing time. The technique was applied to five real image sets which are obtained from the two different modalities and the satisfactory results are obtained. Some experimental results are shown with discussion.