Recognition of Brain Tumors Using Deep Neural Networks Models
DOI:
https://doi.org/10.48001/978-81-980647-5-2-6Keywords:
Brain Tumor, Deep Learning, CNN, VGG-16, ResNet-152, InceptionV2Abstract
The identification of brain tumors is a significant issue in healthcare. A brain tumor is an abnormal tissue mass where cells multiply rapidly and uncontrollably. Image segmentation helps identify the tumor regions in the brain using MRI scans. Early detection of brain tumors is essential, which can be achieved with machine learning and deep learning algorithms. Our research used different deep learning methods, including VGG-16, ResNet-152, Inception-V3, Inception ResNet-V2, and a Custom Convolution neural networks model to categorize brain tumors. The sample dataset for our research consisted of 1085 tumorous and 980 non-tumorous images from the Kaggle online database. Among all the models, VGG-16 performed the best and achieved 98\% accurateness in classifying brain tumors.
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Abdelaziz Ismael, S. A., Mohammed, A., & Hefny, H. (2020). An enhanced deep learning approach for brain cancer MRI images classification using residual networks. Artificial Intelligence in Medicine, 102. https://doi.org/10.1016/j.artmed.2019.101779
Abdulbaqi, H. S., Jafri, M. Z. M., Omar, A. F., Mustafa, I. S. B., & Abood, L. K. (2014). Detecting brain tumor in Magnetic Resonance Images using Hidden Markov Random Fields and Threshold techniques. 2014 IEEE Student Conference on Research and Development, SCOReD 2014. https://doi.org/10.1109/SCORED.2014.7072963
Al-Azzawi, N. A., & Sabir, M. K. (2015). A superior achievement of brain tumor detection using segmentation based on F-transform. 2015 World Symposium on Computer Networks and Information Security, WSCNIS 2015. https://doi.org/10.1109/WSCNIS.2015.7368302
Amin, J., Sharif, M., Gul, N., Raza, M., Anjum, M. A., Nisar, M. W., & Bukhari, S. A. C. (2020). Brain Tumor Detection by Using Stacked Autoencoders in Deep Learning. Journal of Medical Systems, 44(2). https://doi.org/10.1007/s10916-019-1483-2
Amin, J., Sharif, M., Raza, M., Saba, T., & Anjum, M. A. (2019). Brain tumor detection using statistical and machine learning methods. Computer Methods and Programs in Biomedicine, 177, 69–79. https://doi.org/10.1016/j.cmpb.2019.05.015
Arbane, M., Benlamri, R., Brik, Y., & Djerioui, M. (2021). Transfer Learning for Automatic Brain Tumor Classification Using MRI Images. 2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-Being, IHSH 2020, 210–214. https://doi.org/10.1109/IHSH51661.2021.9378739
Bhanothu, Y., Kamalakannan, A., & Rajamanickam, G. (2020). Detection and Classification of Brain Tumor in MRI Images using Deep Convolutional Network. 2020 6th International Conference on Advanced Computing and Communication Systems, ICACCS 2020, 248–252. https://doi.org/10.1109/ICACCS48705.2020.9074375
Chato, L., & Latifi, S. (2017). Machine Learning and Deep Learning Techniques to Predict Overall Survival of Brain Tumor Patients using MRI Images. Proceedings - 2017 IEEE 17th International Conference on Bioinformatics and Bioengineering, BIBE 2017, 2018-Janua, 9–14. https://doi.org/10.1109/BIBE.2017.00-86
Chen, H., Qin, Z., Ding, Y., Tian, L., & Qin, Z. (2020). Brain tumor segmentation with deep convolutional symmetric neural network. Neurocomputing, 392, 305–313. https://doi.org/10.1016/j.neucom.2019.01.111
Choudhury, C. L., Mahanty, C., Kumar, R., & Mishra, B. K. (2020). Brain Tumor Detection and Classification Using Convolutional Neural Network and Deep Neural Network. 2020 International Conference on Computer Science, Engineering and Applications, ICCSEA 2020. https://doi.org/10.1109/ICCSEA49143.2020.9132874
Deepak, S., & Ameer, P. M. (2021). Automated Categorization of Brain Tumor from MRI Using CNN Features and SVM. Journal of Ambient Intelligence and Humanized Computing, 12(8), 8357–8369. https://doi.org/10.1007/s12652-020-02568-w
Havaei, M., Axel, D., David, W.-F., Antoine, B., Aaron, C., Yoshua, B., Chris, P., Pierre-Marc, J., & Hugo, L. (2017). Brain tumor segmentation with deep neural networks. Medical Image Analysis, 18–31.
Jia, Z., & Chen, D. (2024). Brain Tumor Identification and Classification of MRI Images Using Deep Learning Techniques. IEEE Access. https://doi.org/10.1109/ACCESS.2020.3016319
Khan, A. H., Abbas, S., Khan, M. A., Farooq, U., Khan, W. A., Siddiqui, S. Y., & Ahmad, A. (2022). Intelligent Model for Brain Tumor Identification Using Deep Learning. Applied Computational Intelligence and Soft Computing, 2022. https://doi.org/10.1155/2022/8104054
Madhupriya, G., Guru Narayanan, M., Praveen, S., & Nivetha, B. (2019). Brain Tumor Segmentation with Deep Learning Technique. Proceedings of the International Conference on Trends in Electronics and Informatics, ICOEI 2019, 2019-April, 758–763. https://doi.org/10.1109/ICOEI.2019.8862575
Mohmmad, S., & Sanampudi, S. K. (2023). Tree Cutting Sound Detection Using Deep Learning Techniques Based on Mel Spectrogram and MFCC Features. Lecture Notes in Networks and Systems, 612, 497–512. https://doi.org/10.1007/978-981-19-9228-5_42
Mohsen, H., El-Dahshan, E.-S. A., El-Horbaty, E.-S. M., & Salem, A.-B. M. (2018). Classification using deep learning neural networks for brain tumors. Future Computing and Informatics Journal, 3(1), 68–71. https://doi.org/10.1016/j.fcij.2017.12.001
Pereira, S., Pinto, A., Alves, V., & Silva, C. A. (2016). Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images. IEEE Transactions on Medical Imaging, 35(5), 1240–1251. https://doi.org/10.1109/TMI.2016.2538465
Rammurthy, D., & Mahesh, P. K. (2022). Whale Harris Hawks Optimization Based Deep Learning Classifier for Brain Tumor Detection Using MRI Images. Journal of King Saud University - Computer and Information Sciences, 34(6), 3259–3272. https://doi.org/10.1016/j.jksuci.2020.08.006
Rulaningtyas, R., & Ain, K. (2009). Edge Detection for Brain Tumor Pattern Recognition. International Conference on Instrumentation, Communication, Information Technology, and Biomedical Engineering 2009, ICICI-BME 2009. https://doi.org/10.1109/ICICI-BME.2009.5417299
Saba, T., Sameh Mohamed, A., El-Affendi, M., Amin, J., & Sharif, M. (2020). Brain Tumor Detection Using Fusion of Hand Crafted and Deep Learning Features. Cognitive Systems Research, 59, 221–230. https://doi.org/10.1016/j.cogsys.2019.09.007
Sajid, S., Hussain, S., & Sarwar, A. (2019). Brain Tumor Detection and Segmentation in MR Images Using Deep Learning. Arabian Journal for Science and Engineering, 44(11), 9249–9261. https://doi.org/10.1007/s13369-019-03967-8
Siar, M., & Teshnehlab, M. (2019). Brain Tumor Detection Using Deep Neural Network and Machine Learning Algorithm. 2019 9th International Conference on Computer and Knowledge Engineering, ICCKE 2019, 363–368. https://doi.org/10.1109/ICCKE48569.2019.8964846
Wang, G., Li, W., Ourselin, S., & Vercauteren, T. (2019). Automatic Brain Tumor Segmentation Using Convolutional Neural Networks with Test-Time Augmentation. Lecture Notes in Computer Science, 11384 LNCS, 61–72. https://doi.org/10.1007/978-3-030-11726-9_6
Woźniak, M., Siłka, J., & Wieczorek, M. (2023). Deep Neural Network Correlation Learning Mechanism for CT Brain Tumor Detection. Neural Computing and Applications, 35(20), 14611–14626. https://doi.org/10.1007/s00521-021-05841-x
