Image quality assessment of advanced reconstruction algorithm for point-of-care MRI scanner.
Elizabeth A KrupinskiDeAngelo HarrisLori R ArlinghausJo SchlemperMichal SofkaPublished in: Journal of medical imaging (Bellingham, Wash.) (2023)
The deep learning (DL)-based reconstruction scheme to improve pMRI was successful for hemorrhage, but for acute ischemic stroke the scheme could still be improved. For neurocritical care especially in remote and/or resource poor locations, pMRI has significant clinical utility, although radiologists should be aware of limitations of low-field MRI devices in overall quality and take that into account when diagnosing. As an initial triage to aid in the decision of whether to transport or keep patients on site, pMRI images likely provide enough information.
Keyphrases
- deep learning
- image quality
- acute ischemic stroke
- end stage renal disease
- artificial intelligence
- magnetic resonance imaging
- contrast enhanced
- convolutional neural network
- computed tomography
- newly diagnosed
- machine learning
- healthcare
- ejection fraction
- emergency department
- chronic kidney disease
- palliative care
- quality improvement
- diffusion weighted imaging
- prognostic factors
- peritoneal dialysis
- magnetic resonance
- patient reported outcomes
- dual energy
- chronic pain
- health information