Detection of Brain Cancer using Machine Learning Techniques a Review
|International Journal of Computer Science and Engineering|
|© 2022 by SSRG - IJCSE Journal|
|Volume 9 Issue 9|
|Year of Publication : 2022|
|Authors : G. R. Meghana, Suresh Kumar Rudrahithlu, K. C. Shilpa|
How to Cite?
G. R. Meghana, Suresh Kumar Rudrahithlu, K. C. Shilpa, "Detection of Brain Cancer using Machine Learning Techniques a Review," SSRG International Journal of Computer Science and Engineering , vol. 9, no. 9, pp. 12-18, 2022. Crossref, https://doi.org/10.14445/23488387/IJCSE-V9I9P102
The segmentation and prediction of a brain tumour in medical image processing is a critical step. Early detection of brain tumours is critical for enhancing treatment options and boosting patient survival rates. Manual segmentation of brain tumours for cancer detection is challenging and time-consuming from enormous amounts of MRI data obtained in clinical practice. There is a demand for automated brain tumour detection. Classification and segmentation of brain tumours using MRI data is the focus of this work. Deep learning and machine learning approaches for automated segmentation and prediction have recently gained popularity since they provide cutting-edge results and are more suited to dealing with this challenge. MRI-based image data may also be processed efficiently and objectively using deep learning approaches. This paper surveys the thirty papers, including various machine and deep learning methods that can predict the brain tumor.
Brain tumor, MRI, Machine learning, Deep learning.
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