深度学习
人工智能
分割
磁共振成像
计算机科学
脑瘤
机器学习
图像分割
医学
放射科
病理
作者
Md Kamrul Hasan Khan,Wenjing Guo,Jie Liu,Fan Dong,Zoe Li,Tucker A. Patterson,Huixiao Hong
标识
DOI:10.1177/15353702231214259
摘要
Brain tumors are often fatal. Therefore, accurate brain tumor image segmentation is critical for the diagnosis, treatment, and monitoring of patients with these tumors. Magnetic resonance imaging (MRI) is a commonly used imaging technique for capturing brain images. Both machine learning and deep learning techniques are popular in analyzing MRI images. This article reviews some commonly used machine learning and deep learning techniques for brain tumor MRI image segmentation. The limitations and advantages of the reviewed machine learning and deep learning methods are discussed. Even though each of these methods has a well-established status in their individual domains, the combination of two or more techniques is currently an emerging trend.
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