Title: Efficient T2 brain region extraction algorithm using morphological operation and overlapping test from 2D and 3D MRI images
Authors: Vandana Shah; Vijay Chourasia; Ravindra Kshirsagar
Addresses: Department of Electronics and Communication Engineering, Manoharbhai Patel Institute of Engineering and Technology, Gondia – 441614, India ' Department of Electronics and Communication Engineering, Manoharbhai Patel Institute of Engineering and Technology, Gondia – 441614, India ' Department of Electronics and Communication Engineering, Priyadarshini Indira Gandhi College of Engineering, Hingna Road – 440019, Nagpur, India
Abstract: The main purpose of segmentation in MRI images is to diagnose the problems in the normal brain anatomy and to find the location of tumour. Many of the algorithms have been found in recent years which aid to segment the medical images and identify the diseases. This paper proposes a novel 3D brain extraction algorithm (3D-BEA) for segmentation of MRI images to extract the exact brain region. Transverse relaxation time (T2) weighted images are used as an input for the development of algorithm as these images provide bright compartments and dark fat tissues in the MRI brain region. The images are first denoised and smoothed for further processing. The final brain volume has been generated using this 3D-BEA process. The result of this developed proposed algorithm is validated by comparing proposed algorithm with the results of the existing segmentation algorithm.
Keywords: segmentation; morphological operations; clustering; k-means clustering; fuzzy c-means clustering; brain extraction algorithm; Riddler's thresholding; diffusion process; LCC; brain slices.
International Journal of Biomedical Engineering and Technology, 2021 Vol.35 No.4, pp.382 - 399
Received: 16 Nov 2017
Accepted: 27 Feb 2018
Published online: 29 Apr 2021 *