A Novel Approach to Detect Brain Tumor Using CNN model of Deep Learning


Praful Pardhi
Navya Verma
Nikunj Loya
Kartik Agrawal


A tumor is a mass of tissue generated by the aggregation of aberrant cells that continue to grow, and the brain is the most essential organ in the human body, responsible for controlling and regulating all critical life activities for the body. A brain tumor is either formed in the brain or has migrated. Yet, no reason has been found for developing brain tumors. Though brain tumors are uncommon (approximately 1.8 percent of all reported cancers), the death risk of malignant brain tumors is particularly high due to the tumor’s location in the body’s most essential organ. To reduce the mortality rate, it is critical to accurately detect brain tumors at an early stage. As a result, we’ve proposed a computer-assisted radiology method for assessing brain tumors from MRI scans for
brain tumor diagnostic management. In this research paper, we developed a model that uses the Watershed technique to segment images, extract features, and then use deep learning to detect cancers with high accuracy. 


How to Cite
Pardhi, P., Navya Verma, Loya, N., & Agrawal , K. . (2023). A Novel Approach to Detect Brain Tumor Using CNN model of Deep Learning. International Journal of Next-Generation Computing, 14(1). https://doi.org/10.47164/ijngc.v14i1.1041


  1. Al-Ayyoub, M., Husari, G., Darwish, O., and Alabed-alaziz, A. 2012. Machine learning approach for brain tumor detection. In Proceedings of the 3rd international conference on information and communication systems. 1–4. DOI: https://doi.org/10.1145/2222444.2222467
  2. Bathe, Ms Sethiya, M. . K. P. 2019. Brain tumor detection. IJARCCE. DOI: https://doi.org/10.17148/IJARCCE.2019.8312
  3. Janecek, A., Gansterer, W., Demel, M., and Ecker, G. 2008. On the relationship between feature selection and classification accuracy. In New challenges for feature selection in data mining and knowledge discovery. PMLR, 90–105.
  4. Kora, P., Mohammed, S., Teja, M. J. S., Kumari, C. U., Swaraja, K., and Meenakshi, K. 2021. Brain tumor detection with transfer learning. In 2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC). IEEE, 443–446. DOI: https://doi.org/10.1109/I-SMAC52330.2021.9640678
  5. Kumbhar. 2021. Brain tumor detection system. International Journal for Research in Applied Science and Engineering Technology. DOI: https://doi.org/10.22214/ijraset.2021.38286
  6. Shivdikar, Adish Shirke, M. . V. I. . U. 2022. Brain tumor detection using deep learning. International Journal for Research in Applied Science and Engineering Technology 10. DOI: https://doi.org/10.22214/ijraset.2022.40710
  7. Sonsare, P., Pardhi, P., and Khedgaonkar, R. 2021. Leaf infection detection using fuzzy support vector machine. International Journal of Next-Generation Computing 12, 5.