AI-Enhanced Handheld Ultrasound Images Boost Carotid Plaque Detection
A new study has shown that handheld ultrasound imaging methods enhanced with artificial intelligence models strengthen plaque detection in primary healthcare screenings.
According to a new study published in the Annals of Family Medicine, the enhancement of handheld ultrasound images by an artificial intelligence-based super-resolution model increases the detection rate of carotid plaques in community screenings.
Scope of the Research
The study published in the Annals of Family Medicine examines the improvement of handheld ultrasound imaging methods with the help of artificial intelligence. Experts state that this approach supports risk stratification in primary healthcare services.
Hyper-CycleGAN Model
The super-resolution model called Hyper-CycleGAN, developed by the researchers, works on static images transferred from the device. Rather than making a direct diagnosis, the model ensures that boundaries are seen more clearly.
Detection Rates
According to the findings, AI-enhanced images succeeded in showing 94.8% of plaques, compared to the 87.6% rate in standard screenings.
Additional Plaque Detection
Following the AI enhancement, the majority of the additionally detected plaques consisted of small or low-contrast structures with mild stenosis.
Support Tool Role
The authors emphasize that AI-enhanced handheld ultrasound technology is not an independent test on its own, but rather serves as an important support tool for experts.