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X-ray Photon-Counting Data Correction through Deep Learning
RPI ID: 2020-047-201 Innovation Summary: A deep learning-based method is introduced to correct distortions in photon-counting X-ray imaging data. The system compensates for spectral distortions and pile-up effects that degrade image quality in photon-counting detectors. Neural networks are trained to reconstruct corrected images from raw detector outputs,...
Published: 3/10/2026   |   Inventor(s): Mengzhou Li, David Rundle, Ge Wang
Keywords(s): charge splitting, deep learning, PCD data correction, PCDs, photon-counting detector, pulse pile-up
Category(s): Biotechnology and the Life Sciences