Friday, 25 February 2022

Comparative Analysis of Automatic Brain Tumor Segmentation Techniques Using Watershed, Region Growing and K-Means Clustering | Chapter 17 | Issues and Developments in Medicine and Medical Research Vol. 8

 Image segmentation is an important and demanding component in automatic recognition systems for medical images in the broad field of medical image processing. Medical pictures obtained from a variety of sources, including computed tomography (CT), magnetic resonance imaging (MRI), and others, will be used for diagnosis. The goal of this research is to give a thorough examination of several brain tumour segmentation methods. A comparison of these various segmentation conventions has been carried out. The numerous picture segmentation approaches K-Means Clustering, Watershed, and Region are discussed in this work. Methods for detecting brain tumours from sample MRI images of the brain are being developed.



Author(S) Details


Arati Kothari
Department of Computer Science, Gulbarga University, Kalaburagi, Karnataka, India.

View Book:- https://stm.bookpi.org/IDMMR-V8/article/view/5815

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