Review of Automated Computerized Methods for Brain Tumor Segmentation and Classification

Author(s): Umaira Nazar, Muhammad Attique Khan, Ikram Ullah Lali, Hong Lin*, Hashim Ali, Imran Ashraf, Junaid Tariq

Journal Name: Current Medical Imaging
Formerly: Current Medical Imaging Reviews

Volume 16 , Issue 7 , 2020

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Graphical Abstract:


Recently, medical imaging and machine learning gained significant attention in the early detection of brain tumor. Compound structure and tumor variations, such as change of size, make brain tumor segmentation and classification a challenging task. In this review, we survey existing work on brain tumor, their stages, survival rate of patients after each stage, and computerized diagnosis methods. We discuss existing image processing techniques with a special focus on preprocessing techniques and their importance for tumor enhancement, tumor segmentation, feature extraction and features reduction techniques. We also provide the corresponding mathematical modeling, classification, performance matrices, and finally important datasets. Last but not least, a detailed analysis of existing techniques is provided which is followed by future directions in this domain.

Keywords: Brain tumor, preprocessing, tumor segmentation, feature extraction, classification, future trends.

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Article Details

Year: 2020
Page: [823 - 834]
Pages: 12
DOI: 10.2174/1573405615666191120110855
Price: $65

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