Our latest study “Estimate and compensate head motion in non-contrast head CT scans using partial angle reconstruction and deep learning” led by Zhennong Chen and Dufan Wu takes on the challenge of imperfections in head motion artifacts in head CT! With combined power of “partial-angle reconstruction” and deep learning, they’ve achieved a breakthrough in motion artifact reduction in head CT.
Check out some image examples to see the dramatic enhancements in the last column! And they’re not stopping there – their team is already pushing the boundaries further, aiming to replicate these advancements without relying on CT sinogram data. Stay Tuned!
CAMCA Paper Published in the American Association of Physicists in Medicine