Automatic 3D Registration of CT-MR Head and Neck Images With Surface Matching

Abstract

Radiotherapy is a major treatment for head and neck cancer. Currently, computed tomography (CT) is utilized to delineate the target area and make radiotherapy plans. Compared with CT images, magnetic resonance (MR) images have excellent soft tissue contrast, which can distinguish normal surrounding tissues. It is necessary to register MR and CT images since it helps physicists to improve the accuracy of radiotherapy plans. Most of the current registrations require manual intervention to select regions of interest, which increases the workload of doctors and the time of registration to a certain extent. In this paper, an automatic registration method is proposed to delineate the regions of interest. Herein, surface meshes are extracted from the CT and MR images and utilized to perform the surface matching, then the regions of interest are extracted automatically by calculating the overlapped regions between the surface mesh of the surface-aligned MR images and CT images. Furthermore, a multi-level resolution registration mechanism is utilized to improve the registration speed. Surface matching is performed using low-resolution images to obtain transformation parameters as initial parameters for rigid registration followed by deformable registration. The experiments demonstrate that our proposed method performs better in the registration speed and accuracy over the conventional methods of delineating regions of interest manually.