文章基本信息

标题：Overview of Multi-Modal Brain Tumor MR Image Segmentation
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作者：Wenyin Zhang ; Yong Wu ; Bo Yang 等
期刊名称：Healthcare
电子版ISSN：2227-9032
出版年度：2021
卷号：9
期号：8
DOI：10.3390/healthcare9081051
语种：English
出版社：MDPI Publishing
摘要：The precise segmentation of brain tumor images is a vital step towards accurate diagnosis and effective treatment of brain tumors. Magnetic Resonance Imaging (MRI) can generate brain images without tissue damage or skull artifacts, providing important discriminant information for clinicians in the study of brain tumors and other brain diseases. In this paper, we survey the field of brain tumor MRI images segmentation. Firstly, we present the commonly used databases. Then, we summarize multi-modal brain tumor MRI image segmentation methods, which are divided into three categories: conventional segmentation methods, segmentation methods based on classical machine learning methods, and segmentation methods based on deep learning methods. The principles, structures, advantages and disadvantages of typical algorithms in each method are summarized. Finally, we analyze the challenges, and suggest a prospect for future development trends.
关键词：enimage segmentation;brain tumor;magnetic resonance imaging;multi-modality