Generation and evaluation of an MRI statistical organ atlas in the head-neck region

Abstract

Segmenting organs in MRI images is a common task in medical practice where image registration techniques can be used in the preprocessing steps to reduce the required interactivity. This is especially true in the head and neck region where large variability of shape and size of organs is present among patients. When an image database of MRI images and segmented organ contours are available, these can be used to build probability atlases in a selected reference frame. The atlas data can then be transformed to the coordinate systems of studies to be segmented applying the transformations in the inverse direction. In this paper two registration approaches for atlas building are evaluated and compared. Separate atlases for 6 organs (spinal cord, trachea, carotis, jugularis, parotis, sternocleidomastoid muscle — SCM) are built from 15 MRI T2 weighted Fast Relaxation Fast Spin Echo (FRFSE) studies using expert segmented organ contours and evaluated using further 15 such studies. The evaluation takes into account the overlap of the expert segmented organ regions and the transformed probability atlases, the discrimination capabilities of the atlases in the carotis-jugularis region, and the errors induced by the inverse registration approach. The results show the superiority of the multiresolution B-Spline transformation implemented by the elastix package against a less flexible, composite transformation formed using scaled rigid + single resolution B-Spline approach. The presented framework can be used for e.g., determining regions of interests (ROIs) as a preprocessing step of learning based fully automatic segmentation approaches.