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Current Medical Imaging

Editor-in-Chief

ISSN (Print): 1573-4056
ISSN (Online): 1875-6603

Review Article

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 and Junaid Tariq

Volume 16 , Issue 7 , 2020

Page: [823 - 834] Pages: 12

DOI: 10.2174/1573405615666191120110855

Price: $65

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.

Graphical Abstract
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