Application of Automatic Image Registration in a Segmentation Framework of Pelvic CT Images

Abstract

In radiation treatment (RT) planning, clinicians must trace the outline of a few critical structures on a large number of images. Using automated image segmentation could save tremendous time and effort. Segmentation of the organs near the pubic bone (prostate and bladder) is an important and challenging task: Some of the neighboring organs have similar density values in the CT images and the border between the different organs is hardly visible.

In a segmentation framework, transforming a CT study to a common reference frame is used in two tasks: For statistical atlas (model) generation, and in the clinical application, establishing the voxel-to-voxel correspondence between the study and the model. In these cases precise alignment of all anatomical structures is not crucial, the focus is on proper alignment of the pubic bone area and fast execution. Our proposed method solves this by a new, two step process based on a voxel similarity-based registration algorithm.

This work was supported by GE Medical Systems.