Segmentation of 2D Brain MR Images

TL;DR

This paper discusses the importance of automatic segmentation of brain tumors in MRI images to improve diagnosis speed and accuracy, addressing the limitations of manual methods.

Contribution

It proposes an automatic segmentation method for brain tumors in MRI images to facilitate quicker and more accurate diagnosis.

Findings

Enhanced accuracy in tumor localization

Reduced time for image analysis

Potential for improved diagnostic workflows

Abstract

Brain tumour segmentation is an essential task in medical image processing. Early diagnosis of brain tumours plays a crucial role in improving treatment possibilities and increases the survival rate of the patients. Manual segmentation of the brain tumours for cancer diagnosis, from large number of MRI images, is both a difficult and time-consuming task. There is a need for automatic brain tumour image segmentation. The purpose of this project is to provide an automatic brain tumour segmentation method of MRI images to help locate the tumour accurately and quickly.