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Open Access

A Survey of MRI-Based Brain Tumor Segmentation Methods

Jin LiuMin LiJianxin Wang( )Fangxiang WuTianming LiuYi Pan
School of Information Science and Engineering, Central South University, Changsha 410083, China.
Department of Mechanical Engineering and Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, SK S7N 5A9, Canada.
Department of Computer Science, University of Georgia, Boyd 420, Athens, GA 30602, USA.
Department of Computer Science, Georgia State University, Atlanta, GA 30302-3994, USA.
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Abstract

Brain tumor segmentation aims to separate the different tumor tissues such as active cells, necrotic core, and edema from normal brain tissues of White Matter (WM), Gray Matter (GM), and Cerebrospinal Fluid (CSF). MRI-based brain tumor segmentation studies are attracting more and more attention in recent years due to non-invasive imaging and good soft tissue contrast of Magnetic Resonance Imaging (MRI) images. With the development of almost two decades, the innovative approaches applying computer-aided techniques for segmenting brain tumor are becoming more and more mature and coming closer to routine clinical applications. The purpose of this paper is to provide a comprehensive overview for MRI-based brain tumor segmentation methods. Firstly, a brief introduction to brain tumors and imaging modalities of brain tumors is given. Then, the preprocessing operations and the state of the art methods of MRI-based brain tumor segmentation are introduced. Moreover, the evaluation and validation of the results of MRI-based brain tumor segmentation are discussed. Finally, an objective assessment is presented and future developments and trends are addressed for MRI-based brain tumor segmentation methods.

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Tsinghua Science and Technology
Pages 578-595

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Cite this article:
Liu J, Li M, Wang J, et al. A Survey of MRI-Based Brain Tumor Segmentation Methods. Tsinghua Science and Technology, 2014, 19(6): 578-595. https://doi.org/10.1109/TST.2014.6961028

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Received: 16 June 2014
Accepted: 23 June 2014
Published: 20 November 2014
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