Artificial intelligence applied to fetal MRI: A scoping review of current research.
Riwa MeshakaTrevor GauntSusan Cheng ShelmerdinePublished in: The British journal of radiology (2022)
Artificial intelligence (AI) is defined as the development of computer systems to perform tasks normally requiring human intelligence. A subset of AI, known as machine learning (ML), takes this further by drawing inferences from patterns in data to 'learn' and 'adapt' without explicit instructions meaning that computer systems can 'evolve' and hopefully improve without necessarily requiring external human influences. The potential for this novel technology has resulted in great interest from the medical community regarding how it can be applied in healthcare. Within radiology, the focus has mostly been for applications in oncological imaging, although new roles in other subspecialty fields are slowly emerging.In this scoping review, we performed a literature search of the current state-of-the-art and emerging trends for the use of artificial intelligence as applied to fetal magnetic resonance imaging (MRI). Our search yielded several publications covering AI tools for anatomical organ segmentation, improved imaging sequences and aiding in diagnostic applications such as automated biometric fetal measurements and the detection of congenital and acquired abnormalities. We highlight our own perceived gaps in this literature and suggest future avenues for further research. It is our hope that the information presented highlights the varied ways and potential that novel digital technology could make an impact to future clinical practice with regards to fetal MRI.
Keyphrases
- artificial intelligence
- deep learning
- machine learning
- magnetic resonance imaging
- big data
- healthcare
- contrast enhanced
- endothelial cells
- convolutional neural network
- high resolution
- systematic review
- diffusion weighted imaging
- clinical practice
- computed tomography
- mental health
- induced pluripotent stem cells
- current status
- pluripotent stem cells
- working memory
- human health
- physical activity
- social support
- risk assessment
- prostate cancer
- climate change
- health information
- data analysis
- social media
- photodynamic therapy
- quantum dots
- real time pcr
- high throughput