AI reconstruction could become standard of care for abdominal DECT

A group led by Jingyu Zhong of Shanghai Jiao Tong University School of Medicine in China prospectively evaluated the portal-venous phase images in abdominal DECT of 47 participants with 84 lesions, reconstructing the raw data with traditional reconstruction methods and using deep learning-based image reconstruction at three different strengths. The team found that the deep-learning approach at high strength yielded better results.

“[Deep-learning image reconstruction at high strength] could be safely recommended as a new standard for routine low-keV [virtual monoenergetic image]…

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