Atlas-Based Segmentation Pipelines on 3D Brain MR Images: A Preliminary Study

Abstract

Three dimensional structural MR imaging is a high-resolution imaging technique used in the detection and follow up of neurological disorders. Rigid changes in the brain are usually interpreted and reported manually by radiologists using MR images. The results of manual interpretation may vary with respect to the experts. At the same time, measurement and segmentation of the brain regions and the manual evaluation of the volume changes are a difficult process. With the increase of numerical methods, automated and semi-automated package programs have been developed for the analysis of brain measurements. These programs use electronic brain atlases or tissue probability maps. However, since the package programs have a lot of analysis time and give only certain outputs, they may be disadvantaged in the use of segmentation and measurement of brain regions. Hence, special pipelines are needed especially to obtain valuable features for artificial intelligence and classification studies. In this study, we propose pipelines to segment 3D certain brain regions, which will help to find the basic features such as volume changes, intensity variations, symmetry deteriorations, and tissue changes. With these pipelines, 3D segmentation of the brain regions defined in the atlas can be performed and normalized. It is aimed to use these studies as a preliminary study in order to quantitatively determine the basic changes in the brain by performing the volume of interest methods and to formulate a decision support system.