Automated fatty liver disease detection in point-of-care ultrasound B-mode images.
Miriam Naim IbrahimRaul Blázquez-GarcíaAdi LightstoneFankun MengMamatha BhatAhmed El KaffasUkwatta ErangaPublished in: Journal of medical imaging (Bellingham, Wash.) (2023)
Despite minimal POCUS acquisition training, and low-quality B-mode images, it is possible to detect steatosis using DL algorithms. Implementation of this algorithm in POCUS software may offer an accessible, low-cost steatosis screening technology, for use by non-expert health care personnel.
Keyphrases
- deep learning
- low cost
- healthcare
- convolutional neural network
- insulin resistance
- machine learning
- high fat diet
- high fat diet induced
- quality improvement
- primary care
- magnetic resonance imaging
- adipose tissue
- label free
- clinical practice
- loop mediated isothermal amplification
- skeletal muscle
- type diabetes
- virtual reality
- real time pcr
- optical coherence tomography
- fatty acid
- high throughput
- affordable care act