Brain tumor detection and classification using machine learning: a comprehensive survey

被引:0
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作者
Javaria Amin
Muhammad Sharif
Anandakumar Haldorai
Mussarat Yasmin
Ramesh Sundar Nayak
机构
[1] University of Wah,Department of Computer Science
[2] COMSATS University Islamabad,Department of Computer Science
[3] Sri Eshwar College of Engineering,Department of Computer Science and Engineering
[4] Canara Engineering College,Department of IS&E
来源
关键词
Brain imaging modalities; Segmentation; Feature extraction; MRI; Stroke;
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学科分类号
摘要
Brain tumor occurs owing to uncontrolled and rapid growth of cells. If not treated at an initial phase, it may lead to death. Despite many significant efforts and promising outcomes in this domain, accurate segmentation and classification remain a challenging task. A major challenge for brain tumor detection arises from the variations in tumor location, shape, and size. The objective of this survey is to deliver a comprehensive literature on brain tumor detection through magnetic resonance imaging to help the researchers. This survey covered the anatomy of brain tumors, publicly available datasets, enhancement techniques, segmentation, feature extraction, classification, and deep learning, transfer learning and quantum machine learning for brain tumors analysis. Finally, this survey provides all important literature for the detection of brain tumors with their advantages, limitations, developments, and future trends.
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页码:3161 / 3183
页数:22
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