article

MRI Brain Images Classification: A Multi-Level Threshold Based Region Optimization Technique

Authors:

P. MarikkannuAuthors Info & Claims

Journal of Medical Systems, Volume 42, Issue 4

Pages 1 - 12

https://doi.org/10.1007/s10916-018-0915-8

Published: 01 April 2018 Publication History

Abstract

Medical image processing is the most challenging and emerging field nowadays. Magnetic Resonance Images (MRI) act as the source for the development of classification system. The extraction, identification and segmentation of infected region from Magnetic Resonance (MR) brain image is significant concern but a dreary and time-consuming task performed by radiologists or clinical experts, and the final classification accuracy depends on their experience only. To overcome these limitations, it is necessary to use computer-aided techniques. To improve the efficiency of classification accuracy and reduce the recognition complexity involves in the medical image segmentation process, we have proposed Threshold Based Region Optimization (TBRO) based brain tumor segmentation. The experimental results of proposed technique have been evaluated and validated for classification performance on magnetic resonance brain images, based on accuracy, sensitivity, and specificity. The experimental results achieved 96.57% accuracy, 94.6% specificity, and 97.76% sensitivity, shows the improvement in classifying normal and abnormal tissues among given images. Detection, extraction and classification of tumor from MRI scan images of the brain is done by using MATLAB software.

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Cited By

Dhole NDixit V(2022)RETRACTED ARTICLE: Review of brain tumor detection from MRI images with hybrid approachesMultimedia Tools and Applications10.1007/s11042-022-12162-181:7(10189-10220)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1007/s11042-022-12162-1
Fang LYao YZhang LWang XZhang Q(2022)Energy functional driven by multiple features for brain lesion segmentationMultimedia Tools and Applications10.1007/s11042-021-11620-681:25(36195-36215)Online publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1007/s11042-021-11620-6
Dixit ANanda A(2022)An improved whale optimization algorithm-based radial neural network for multi-grade brain tumor classificationThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-021-02176-538:11(3525-3540)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1007/s00371-021-02176-5
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Index Terms

MRI Brain Images Classification: A Multi-Level Threshold Based Region Optimization Technique
1. Applied computing
  1. Life and medical sciences
2. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
  2. Machine learning
    1. Learning paradigms
      1. Supervised learning
        Supervised learning by classification
    2. Machine learning approaches
      1. Classification and regression trees

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

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Published In

cover image Journal of Medical Systems

Journal of Medical Systems Volume 42, Issue 4

Mar 2018

211 pages

ISSN:0148-5598

Issue’s Table of Contents

Copyright © Copyright © 2018 Springer Science+Business Media, LLC, part of Springer Nature.

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Plenum Press

United States

Publication History

Published: 01 April 2018

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Cited By

Dhole NDixit V(2022)RETRACTED ARTICLE: Review of brain tumor detection from MRI images with hybrid approachesMultimedia Tools and Applications10.1007/s11042-022-12162-181:7(10189-10220)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1007/s11042-022-12162-1
Fang LYao YZhang LWang XZhang Q(2022)Energy functional driven by multiple features for brain lesion segmentationMultimedia Tools and Applications10.1007/s11042-021-11620-681:25(36195-36215)Online publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1007/s11042-021-11620-6
Dixit ANanda A(2022)An improved whale optimization algorithm-based radial neural network for multi-grade brain tumor classificationThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-021-02176-538:11(3525-3540)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1007/s00371-021-02176-5
Aarthi RHelen Prabha K(2021)Classification of brain neoplasm from multi-modality MRI with the aid of ANFIS classifierMultidimensional Systems and Signal Processing10.1007/s11045-021-00761-432:3(933-957)Online publication date: 1-Jul-2021
https://dl.acm.org/doi/10.1007/s11045-021-00761-4
Sethy PBehera S(2021)A data constrained approach for brain tumour detection using fused deep features and SVMMultimedia Tools and Applications10.1007/s11042-021-11098-280:19(28745-28760)Online publication date: 1-Aug-2021
https://dl.acm.org/doi/10.1007/s11042-021-11098-2
Barranco-Gutiérrez ARostro-Gonzalez H(2020)Machine Learning for Brain Images Classification of Two Language SpeakersComputational Intelligence and Neuroscience10.1155/2020/90454562020Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1155/2020/9045456
Fernandes STanik URajinikanth VKarthik K(2020)A reliable framework for accurate brain image examination and treatment planning based on early diagnosis support for cliniciansNeural Computing and Applications10.1007/s00521-019-04369-532:20(15897-15908)Online publication date: 1-Oct-2020
https://dl.acm.org/doi/10.1007/s00521-019-04369-5

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