research-article

A hybrid approach to segment and detect brain abnormalities from MRI scan

Authors:

S. VijayachitraAuthors Info & Claims

Volume 216, Issue C

https://doi.org/10.1016/j.eswa.2022.119435

Published: 15 April 2023 Publication History

Highlights

•

Segmenting brain abnormality is a complex task.

•

Detecting and segmenting brain abnormal regions from the MRI images.

•

A hybrid approach using GAN, K-means clustering, and Mobile Net v2 architecture.

•

Feature selection by GAN improved the abnormality selection.

•

Performance metrics and comparison shows model was effective.

Abstract

The Detection of brain abnormality is a complex task. The images captured from the MRI scan machines have numerous information, and it is difficult to segment the appropriate information from the images. Earlier studies have shown various challenges in detecting brain abnormalities through image processing. And one among them is the segmentation of the appropriate region with abnormalities. Thus, the paper proposes a hybrid approach using GAN, K-means clustering, and MobileNet to detect brain abnormalities. Here, the GAN is used to generate fake images from the real images of MR scans. This fake image has been enhanced, and it supports segmenting the abnormal zone from the image using K-means clustering. The segmented region is identified and analyzed for the abnormalities using the MobileNet. Finally, the proposed model could detect abnormalities from the MR images of the brain. The performance metrics for the proposed model are measured and compared, which indicates the improved performance of the proposed model.

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Cited By

Kandhway P(2024)A novel adaptive contextual information-based 2D-histogram for image thresholdingExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.122026238:PCOnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.122026
Çetiner HMetlek S(2023)DenseUNet+Journal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2023.10166335:8Online publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1016/j.jksuci.2023.101663

Index Terms

A hybrid approach to segment and detect brain abnormalities from MRI scan
1. Applied computing
  1. Life and medical sciences
2. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Image segmentation
  2. Machine learning

Index terms have been assigned to the content through auto-classification.

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Information & Contributors

Information

Published In

cover image Expert Systems with Applications: An International Journal

Expert Systems with Applications: An International Journal Volume 216, Issue C

Apr 2023

1126 pages

ISSN:0957-4174

Issue’s Table of Contents

Elsevier Ltd.

Publisher

Pergamon Press, Inc.

United States

Publication History

Published: 15 April 2023

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Cited By

Kandhway P(2024)A novel adaptive contextual information-based 2D-histogram for image thresholdingExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.122026238:PCOnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.122026
Çetiner HMetlek S(2023)DenseUNet+Journal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2023.10166335:8Online publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1016/j.jksuci.2023.101663

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