Pushing the limits of low-cost ultralow-field MRI by dual-acquisition deep learning 3D superresolution.
Vick LauLinfang XiaoYujiao ZhaoShi SuYe DingChristopher ManXunda WangChun On Anderson TsangPeng CaoGary Kui Kai LauGilberto Ka Kit LeungAlex T L LeongEd X WuPublished in: Magnetic resonance in medicine (2023)
The proposed dual-acquisition 3D supe-resolution approach advances ULF MRI for quality brain imaging through deep learning of high-field brain data. Such strategy can empower ULF MRI for low-cost brain imaging, especially in point-of-care scenarios or/and in low-income and mid-income countries.
Keyphrases
- low cost
- deep learning
- contrast enhanced
- resting state
- magnetic resonance imaging
- white matter
- high resolution
- functional connectivity
- diffusion weighted imaging
- cerebral ischemia
- mental health
- physical activity
- computed tomography
- climate change
- quality improvement
- brain injury
- multiple sclerosis
- subarachnoid hemorrhage
- mass spectrometry
- electronic health record
- big data
- data analysis