Published Paper Details:

In the field of medical resonance image (MRI) processing the image segmentation is an important and challenging problem in an image analysis. 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. They are then used for extraction of irregular brain masks through threshold implementation which are then compared with the upper and lower slice of the brain images using morphological operations. 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 used for the same purpose. The proposed algorithm will help medical experts to understand and diagnose the tumour area of the patient.