Magnetic resonance image-based brain tumour segmentation methods: A systematic review.
Jayendra Maganbhai BhalodiyaSarah N Lim Choi KeungTheodoros N ArvanitisPublished in: Digital health (2022)
U-Net is a promising deep learning technology for magnetic resonance imaging-based brain tumour segmentation. The community should be encouraged to contribute open-access datasets so training, testing and validation of deep learning algorithms can be improved, particularly for diffusion- and perfusion-weighted magnetic resonance imaging, where there are limited datasets available.
Keyphrases
- deep learning
- contrast enhanced
- magnetic resonance imaging
- magnetic resonance
- convolutional neural network
- artificial intelligence
- resting state
- white matter
- machine learning
- computed tomography
- diffusion weighted imaging
- functional connectivity
- rna seq
- minimally invasive
- healthcare
- mental health
- cerebral ischemia
- blood brain barrier
- brain injury