Brain Tumor Detection Using Deep Learning

Abstract:

Brain tumors are developed as a result of unregulated and fast cell proliferation. It may result in death if not treated in the early stages. The imaging technology used to diagnose brain tumors is known as magnetic resonance imaging (MRI). Early detection of brain tumors is critical in medical practise in order to determine whether the tumor will progress to malignancy. For picture categorization, deep learning is a useful and effective method. Deep learning has been widely used in a variety of sectors, including medical imaging, because its application does not necessitate the expertise of a subject matter expert, but does necessitate a large amount of data and a variety of data in order to produce accurate classification results. The deep learning technique for image categorization is the convolutional neural network (CNN).In this research work , two different models are used to categorize brain tumors and their results were evaluated using performance metrics like accuracy and precision and the results were impressive

• Periodical: Advances in Science and Technology (Volume 124)
• Pages: 37-43
• DOI: https://doi.org/10.4028/p-5d1g8v
• Online since: February 2023
• Authors: S.J.A. Jairam*, D. Lokeshwar, B. Divya, P. Mohamed Fathimal
• Keywords: Brain Tumor, Classification, Deep Learning-Based Tumor Classification, Image Segmentation, Medical Image

References

[1] Javaria Amin, Muhammad Sharif, Anandakumar Haldorai, Mussarat Yasmin, Ramesh Sundar Nayak - Brain tumor detection and classification using machine learning: a comprehensive survey,, Complex & Intelligent Systems, October (2021).

DOI: 10.1007/s40747-021-00563-y

[2] Emrah Irmak - Multi-Classification of Brain Tumor MRI Images Using Deep Convolutional Neural Network with Fully Optimized Framework,, Iranian Journal of Science and Technology, Transactions of Electrical Engineering, 10 April (2021).

DOI: 10.1007/s40998-021-00426-9

[3] G. Hemanth, M. Janardhan and L. Sujihelen, Design and Implementing Brain Tumor Detection Using Machine Learning Approach,, 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI), (2019).

DOI: 10.1109/icoei.2019.8862553

[4] R. D. Shirwaikar, K. Ramesh and A. Hiremath, A survey on Brain Tumor Detection using Machine Learning,, International Conference on Forensics, Analytics, Big Data, Security (FABS), (2021).

DOI: 10.1109/fabs52071.2021.9702583

[5] A. Miglani, H. Madan, S. Kumar and S. Kumar, A Literature Review on Brain Tumor Detection and Segmentation,,, 5th International Conference on Intelligent Computing and Control Systems (ICICCS), (2021).

DOI: 10.1109/iciccs51141.2021.9432342

[6] A. Sinha, A. R P, M. Suresh, N. Mohan R, A. D and A. G. Singerji, Brain Tumor Detection Using Deep Learning,, 2021 Seventh International conference on Bio Signals, Images, and Instrumentation (ICBSII), (2021).

DOI: 10.1109/icbsii51839.2021.9445185

[7] S. Rajkumar, K. Karthick, N. Selvanathan, U. K. B. Saravanan, M. Murali and B. Dhiyanesh, Brain Tumor Detection Using Deep Learning Neural Network for Medical Internet of Things Applications,, 2021 6th International Conference on Communication and Electronics Systems (ICCES), (2021).

DOI: 10.1109/icces51350.2021.9489187

[8] N. M. Dipu, S. A. Shohan and K. M. A Salam, Brain Tumor Detection Using Various Deep Learning Algorithms,, 2021 International Conference on Science & Contemporary Technologies (ICSCT), (2021).

DOI: 10.1109/icsct53883.2021.9642649

[9] G. Hemanth, M. Janardhan and L. Sujihelen, Design and Implementing Brain Tumor Detection Using Machine Learning Approach,, 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI), (2019).

DOI: 10.1109/icoei.2019.8862553

[10] G. Raut, A. Raut, J. Bhagade, J. Bhagade and S. Gavhane, "Deep Learning Approach for Brain Tumor.

DOI: 10.1109/iccdw45521.2020.9318681

[11] Detection and Segmentation," 20International Conference on Convergence to Digital World - Quo Vadis (ICCDW), (2020).

[12] S. Irsheidat and R. Duwairi, Brain Tumor Detection Using Artificial Convolutional Neural Networks,, 2020 11th International Conference on Information and Communication Systems (ICICS), (2020).

DOI: 10.1109/icics49469.2020.239522