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Multimodal Brain Tumor Classification using Capsule Convolution Neural Network with Differential Evolution Optimization Process Cover

Multimodal Brain Tumor Classification using Capsule Convolution Neural Network with Differential Evolution Optimization Process

Open Access
|Dec 2024

References

  1. Miller, K. D., Ostrom, Q. T., Kruchko, C., Patil, N., Tihan, T., Cioffi, G., Fuchs, H. E., Waite, K. A., Jemal, A., Siegel, R. L., Barnholtz-Sloan, J. S. (2021). Brain and other central nervous system tumor statistics, 2021. CA: A Cancer Journal For Clinicians, 71 (5), 381-406. https://doi.org/10.3322/caac.21693
  2. Amin, J., Sharif, M., Raza, M., Saba, T., Anjum, M. A. (2019). Brain tumor detection using statistical and machine learning method. Computer Methods and Programs in Biomedicine, 177 (3), 69-79. https://doi.org/10.1016/j.cmpb.2019.05.015
  3. Ibrahim, I. M., Abdulazeez, A. M. (2021). The role of machine learning algorithms for diagnosing diseases. Journal of Application Science and Technology Trends, 2 (1), 10-19. https://doi.org/10.38094/jastt20179
  4. Jacily Jemila, S., Jayasankar, T. (2011). An automated cancer recognition system for MRI images using neuro fuzzy logic. International Journal of Computer Information Systems, 2 (5), 18-22. ISSN 2229-5208.
  5. Rashid, M., Khan, M. A., Alhaisoni, M., Wang, S.-H., Naqvi, S. R., Rehman, A., Saba, T. (2020). A sustainable deep learning framework for object recognition using multi-layers deep features fusion and selection. Sustainability, 12 (12), 5037. https://doi.org/10.3390/su12125037
  6. Agrawal, T., Choudhary, P., Shankar, A., Singh, P., Diwakar, M. (2024). MultiFeNet: Multi‐scale feature scaling in deep neural network for the brain tumour classification in MRI images. International Journal of Imaging Systems and Technology, 34 (1), e22956. https://doi.org/10.1002/ima.22956
  7. Ranjbarzadeh, R., Zarbakhsh, P., Caputo, A., Tirkolaee, E. B., Bendechache, M. (2024). Brain tumor segmentation based on optimized convolutional neural network and improved chimp optimization algorithm. Computers in Biology and Medicine, 168, 107723. https://doi.org/10.1016/j.compbiomed.2023.107723
  8. Kurdi, S. Z., Ali, M. H., Jaber, M. M., Saba, T., Rehman, A., Damaševičius, R. (2023). Brain tumor classification using meta-heuristic optimized convolutional neural networks. Journal of Personalized Medicine, 13 (2), 181. https://doi.org/10.3390/jpm13020181
  9. Shajin, F. H., Salini, P., Rajesh, P., Nagoji Rao, V. K. (2023). Efficient framework for brain tumour classification using hierarchical deep learning neural network classifier. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 11 (3), 750-757. https://doi.org/10.1080/21681163.2022.2111719
  10. Rahman, T., Islam, M. S. (2023). MRI brain tumor detection and classification using parallel deep convolutional neural networks. Measurement: Sensors, 26, 100694. https://doi.org/10.1016/j.measen.2023.100694
  11. Tazin, T., Sarker, S., Gupta, P., Ayaz, F. I., Islam, S., Khan, M. M., Bourouis, S., Idris, S. A., Alshazly, H. (2023). Retracted: A robust and novel approach for brain tumor classification using convolutional neural network. Computational Intelligence and Neuroscience, 2023, 9760861. https://doi.org/10.1155/2023/9760861
Language: English
Page range: 234 - 238
Submitted on: May 30, 2024
Accepted on: Oct 10, 2024
Published on: Dec 24, 2024
Published by: Slovak Academy of Sciences, Institute of Measurement Science
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open

© 2024 C Senthilkumar, Eatedal Alabdulkreem, Nuha Alruwais, K Suresh, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.