Engineers at Rensselaer Polytechnic Institute (RPI), China's Shanghai First-Imaging Tech, and GE Research have developed a deep neural network that produces spectral images almost as well as dual-energy computed tomography (CT) imaging technology.
The team applied a deep learning algorithm trained on dual-energy CT images to a regular single-spectrum X-ray CT scan.
The model yielded high-quality approximations, with a relative error of less than 2%.
RPI's Ge Wang said, "We hope that this technique will help extract more information from a regular single-spectrum X-ray CT scan, make it more quantitative, and improve diagnosis."
From RPI School of Engineering
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