CT segmentation based on MRI images in context of prostate radiotherapy planning

Abstract

This paper addresses a problem of automatic segmentation of computed tomography (CT) data in context of prostate radiotherapy planning. A new 3D algorithm is proposed in which a prostate is automatically contoured in CT images. The proposed segmentation scenario consists of the following steps: 1) both CT and magnetic resonance (MR) data of a patient are acquired, 2) due to better visibility of soft tissues in MR images, soft organs are segmented in MR data using active contour method (snakes) with additional gradient vector flow enhancement, 3) then obtained 3D contours are mapped from MR to CT images (using mutual information criterion) by means of a flexible registration technique in which global affine transformation is combined with local B-spline free from deformation method. During segmentation of the MR images prior knowledge about a mean ellipsoidal prostate shape, extracted before, plays a role of an addition constraint. Obtained results are compared with manual segmentation done by medical doctors using Dice similarity measure.