IVCVLGNov 5, 2021

Segmentation of 2D Brain MR Images

arXiv:2111.03370v1
Originality Synthesis-oriented
AI Analysis

This addresses the need for faster and more efficient brain tumor diagnosis in medical imaging, but appears incremental as it builds on existing segmentation techniques.

The paper tackles the problem of manual brain tumor segmentation from MRI images, which is time-consuming and difficult, by proposing an automatic method to locate tumors accurately and quickly.

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.

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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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