Enhancement and segmentation of pituitary gland from MR brain images

Abstract

The work herein proposes a framework for semi-automatic segmentation of pituitary gland from MRI brain images. The proposed framework initially uses a fused stationary wavelet transform (SWT) and discrete wavelet transform (DWT) to obtain a high resolution image of the input MRI brain image. After the input MRI brain image enhancement, the method applies thresholding and mathematical morphology to segment the pituitary gland from the input MRI brain image. The proposed algorithm for the same is coded in MATLAB 7.9 on MRI brain images. The segmented pituitary gland obtained using the proposed method is compared with the manually segmented pituitary gland (by an expert), region growing-based brain segmentation and watershed brain segmentation using Jackard's similarity coefficient (JSI) and overlap index (OI). The visual evaluation by a team of radiologists has demonstrated the efficacy of the proposed framework of pituitary gland extraction.