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Performance Improved Hybrid Intelligent System for Medical Image Classification

Authors:

D. Jude Hemanth,

Valentina Emilia BalasAuthors Info & Claims

BCI '15: Proceedings of the 7th Balkan Conference on Informatics Conference

Article No.: 8, Pages 1 - 5

https://doi.org/10.1145/2801081.2801095

Published: 02 September 2015 Publication History

Abstract

Kohonen neural networks are one of the commonly used Artificial Neural Network (ANN) for medical imaging applications. In spite of the numerous advantages, there are some demerits associated with Kohonen neural network which are mostly unexplored. Being an unsupervised neural network, they are mostly dependent on iterations which ultimately affect the accuracy of the overall system. Any iteration dependent ANN may have to face local minima problems also. In this work, this specific problem is solved by proposing a hybrid swarm intelligence- Kohonen approach. The inclusion of Particle Swarm Optimization (PSO) in the training algorithm of Kohonen network provides a convergence condition which eliminates the iteration-dependent nature of Kohonen network. The proposed methodology is tested on Magnetic Resonance (MR) brain tumor image classification. A comparative analysis with the conventional Kohonen network shows the superior nature of the proposed technique in terms of the performance measures.

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Cited By

Sharma RMittal MGupta VVasdev D(2024)Detection of plant leaf disease using advanced deep learning architecturesInternational Journal of Information Technology10.1007/s41870-024-01937-416:6(3475-3492)Online publication date: 29-May-2024
https://doi.org/10.1007/s41870-024-01937-4
Sethuram Rao GVydeki D(2023)Multistage Classification and Segmentation of Brain MR Image Using Modified Soft Computing TechniquesCentral Nervous System Tumors - Primary and Secondary10.5772/intechopen.105908Online publication date: 22-Feb-2023
https://doi.org/10.5772/intechopen.105908
Priyanka Kumar D(2022)Meta-heuristic Techniques to Train Artificial Neural Networks for Medical Image Classification: A ReviewRecent Advances in Computer Science and Communications10.2174/266625581399920091514153415:4Online publication date: May-2022
https://doi.org/10.2174/2666255813999200915141534
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Performance Improved Hybrid Intelligent System for Medical Image Classification
1. Computer systems organization
  1. Architectures
    1. Other architectures
2. Computing methodologies
  1. Machine learning
    1. Machine learning approaches

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cover image ACM Other conferences

BCI '15: Proceedings of the 7th Balkan Conference on Informatics Conference

September 2015

293 pages

ISBN:9781450333351

DOI:10.1145/2801081

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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UCV: University of Craiova

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 September 2015

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BCI '15

BCI '15: 7th Balkan Conference in Informatics

September 2 - 4, 2015

Craiova, Romania

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BCI '15 Paper Acceptance Rate 32 of 74 submissions, 43%;

Overall Acceptance Rate 97 of 250 submissions, 39%

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Cited By

Sharma RMittal MGupta VVasdev D(2024)Detection of plant leaf disease using advanced deep learning architecturesInternational Journal of Information Technology10.1007/s41870-024-01937-416:6(3475-3492)Online publication date: 29-May-2024
https://doi.org/10.1007/s41870-024-01937-4
Sethuram Rao GVydeki D(2023)Multistage Classification and Segmentation of Brain MR Image Using Modified Soft Computing TechniquesCentral Nervous System Tumors - Primary and Secondary10.5772/intechopen.105908Online publication date: 22-Feb-2023
https://doi.org/10.5772/intechopen.105908
Priyanka Kumar D(2022)Meta-heuristic Techniques to Train Artificial Neural Networks for Medical Image Classification: A ReviewRecent Advances in Computer Science and Communications10.2174/266625581399920091514153415:4Online publication date: May-2022
https://doi.org/10.2174/2666255813999200915141534
Sarmah AHazarika AKalita PDev Choudhury B(2017)A subspace projection based feature fusion: An application to EEG clustering2017 International Conference on Signal Processing and Communication (ICSPC)10.1109/CSPC.2017.8305894(472-476)Online publication date: Jul-2017
https://doi.org/10.1109/CSPC.2017.8305894
Hazarika ABhuyan MBarthakur MDutta L(2017)Multi-view learning for classification of EMG template2017 International Conference on Signal Processing and Communication (ICSPC)10.1109/CSPC.2017.8305893(467-471)Online publication date: Jul-2017
https://doi.org/10.1109/CSPC.2017.8305893
Hazarika ABhuyan M(2017)A Twofold Subspace Learning-Based Feature Fusion Strategy for Classification of EMG and EMG Spectrogram ImagesBiologically Rationalized Computing Techniques For Image Processing Applications10.1007/978-3-319-61316-1_4(57-84)Online publication date: 18-Aug-2017
https://doi.org/10.1007/978-3-319-61316-1_4

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