A proposed machine-learning technique can convert ultrasound signals into a skull profile, which could lead to noninvasive imaging for medical treatments in the human brain.
The current best practice is to create individual skull profiles using CT scans or MRI. The profile provides exact knowledge of how the skull affects ultrasound propagation. Still, requiring an additional scan “defeats the ease of ultrasound,” says Yun Jing from Pennsylvania State University. CT and MRI methods are resource and time-intensive, and CT scans expose the brain to harmful radiation.
The researcher team proposed a new method to extract the skull properties using radio-frequency (rf) ultrasound pulses reflecting off a skull.
Read about the proposal: https://physics.aps.org/articles/v14/182
