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Automated localization of Epileptic Focus Using Convolutional Neural Network

Authors:

Junhai WenAuthors Info & Claims

BDET '20: Proceedings of the 2020 2nd International Conference on Big Data Engineering and Technology

Pages 72 - 75

https://doi.org/10.1145/3378904.3378928

Published: 09 April 2020 Publication History

Abstract

Focal cortical dysplasia (FCD) is one of the most common causes of intractable epilepsy. The automatic localization of magnetic resonance (MR) images of epileptic lesions caused by FCD can be performed by using the convolutional neural network (CNN) technology in the field of artificial intelligence, which is helpful for doctors to better diagnose. This study trained a four-layer CNN, including the 8630 learning parameters and three convolutional layers followed by the pooling layer and one full connection layer, and finally, output an image as a disease probability value. The network can classify the MR images with the disease or not, and the accuracy of the final classification of the new data is 92.45%. On the basis of correct classification, the accurate rate of FCD lesions localization can reach 92.86% by using this network.

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Cited By

Ganji ZAzizi SFaraji RZare H(2024)Application of neuroimaging in diagnosis of focal cortical dysplasiaNeurocomputing10.1016/j.neucom.2024.127418580:COnline publication date: 2-Jul-2024
https://dl.acm.org/doi/10.1016/j.neucom.2024.127418
Jiménez-Murillo DCastro-Ospina ADuque-Muñoz LMartínez-Vargas JSuárez-Revelo JVélez-Arango Jde la Iglesia-Vayá M(2023)Automatic Detection of Focal Cortical Dysplasia Using MRI: A Systematic ReviewSensors10.3390/s2316707223:16(7072)Online publication date: 10-Aug-2023
https://doi.org/10.3390/s23167072
Karthika ASubramanian RKarthik S(2022)Using a recurrent neural network with S2 characteristics, efficient identification of localised cortical dysplasiaJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-21246342:6(6293-6306)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/JIFS-212463

Index Terms

Automated localization of Epileptic Focus Using Convolutional Neural Network
1. Computing methodologies
  1. Machine learning
    1. Machine learning algorithms
      1. Regularization

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BDET '20: Proceedings of the 2020 2nd International Conference on Big Data Engineering and Technology

January 2020

126 pages

ISBN:9781450376839

DOI:10.1145/3378904

Copyright © 2020 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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Natl University of Singapore: National University of Singapore
Southwest Jiaotong University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 April 2020

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The National Key R&D Program of China
NSAF

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BDET 2020

BDET 2020: 2020 2nd International Conference on Big Data Engineering and Technology

January 3 - 5, 2020

Singapore, China

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Cited By

Ganji ZAzizi SFaraji RZare H(2024)Application of neuroimaging in diagnosis of focal cortical dysplasiaNeurocomputing10.1016/j.neucom.2024.127418580:COnline publication date: 2-Jul-2024
https://dl.acm.org/doi/10.1016/j.neucom.2024.127418
Jiménez-Murillo DCastro-Ospina ADuque-Muñoz LMartínez-Vargas JSuárez-Revelo JVélez-Arango Jde la Iglesia-Vayá M(2023)Automatic Detection of Focal Cortical Dysplasia Using MRI: A Systematic ReviewSensors10.3390/s2316707223:16(7072)Online publication date: 10-Aug-2023
https://doi.org/10.3390/s23167072
Karthika ASubramanian RKarthik S(2022)Using a recurrent neural network with S2 characteristics, efficient identification of localised cortical dysplasiaJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-21246342:6(6293-6306)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/JIFS-212463

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