IMPROVED SEGMENTATION OF MR BRAIN IMAGES INCLUDING BIAS FIELD CORRECTION BASED ON 3D-CSC

摘要

The 3D Cell Structure Code (3D-CSC) is a fast region growing technique. However, directly adapted for segmentation of magnetic resonance (MR) brain images it has some limitations due to the variability of brain anatomical structure and the degradation of MR images by intensity inhomogeneities and noise. In this paper an improved approach is proposed. It starts with a preprocessing step which contains a 3D Kuwahara filter to reduce noise and a bias correction method to compensate intensity inhomogeneities. Next the 3D-CSC is applied, where a required similarity threshold is chosen automatically. In order to recognize gray and white matter, a histogram-based classification is applied. Morphological operations are used to break small bridges connecting gray value similar non-brain tissues with the gray matter. 8 real and 10 simulated T1-weighted MR images were evaluated to validate the performance of our method.