Machine learning and deep learning for brain tumor MRI image segmentation.
Md Kamrul Hasan KhanWenjing GuoJie LiuFan DongZoe LiTucker A PattersonHuixiao HongPublished in: Experimental biology and medicine (Maywood, N.J.) (2023)
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.
Keyphrases
- deep learning
- machine learning
- magnetic resonance imaging
- contrast enhanced
- artificial intelligence
- convolutional neural network
- diffusion weighted imaging
- big data
- computed tomography
- high resolution
- magnetic resonance
- white matter
- mass spectrometry
- systematic review
- randomized controlled trial
- multiple sclerosis
- fluorescence imaging
- photodynamic therapy
- cerebral ischemia
- combination therapy