Segmentation of brain from MRI head images using modified Chan-Vese active contour model

الملخص EN

In this article, a new segmentation method to extract the brain from T1, T2 and PD-weighted Magnetic Resonance Image (MRI) of human head images based on Modified Chan-Vese (MCV) active contour model is proposed.

This method first segment the brain in the middle slice of the brain volume.

Then, the brain regions of the remaining slices are segmented using the extracted middle brain as a reference.

The input brain image is pre-processed to find the rough brain.

The initial contour for the MCV method is drawn at the center of the segmented rough brain image and is then propagated to reach the brain boundary.

The result of this proposed method is compared with the hand stripped images and found to produce significant results.

The proposed method was tested with 100 volumes of brain images and had accurately segmented the brain regions which are better than the existing methods such as Brain Extraction Tool (BET), Brain Surface Extraction (BSE), Watershed Algorithm (WAT), Hybrid Watershed Algorithm (HWA) and skull stripping using Graph Cuts (GCUT).