Ultrasound imaging of the brain would have a variety of practical applications including real-time images on the operating table, more accurate targeting of brain stimulation tied to emotions and movement, and better mind-controlled software. However, ultrasound beams ricochet around in the skull making imaging extremely difficult. Until now.
According to a recent article from Vanderbilt School of Engineering, Brett Byram is using a $550k National Science Foundation Faculty Early Career Development Grant to do the impossible. Byram, an assistant professor of biomedical engineering, plans to use machine learning to counter distortion and deliver workable images. He believes the applications are endless; the helmet could produce images of the brain as clear as the heart or womb, or better integrate robotic assistance for an ALS patient by detecting targeted blood flow.
.jpg?crop=focalpoint&fit=crop&fp-x=0.5&fp-y=0.5&h=146&w=340)
