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Abstract

Substantial reduction of the radiation dose in computed tomography (CT) imaging is shown using a machine-learning dose-reduction technique. Techniques are provided that (1) enhance low-radiation dosage images, beyond just reducing noise, and (2) may be combined with other approaches, such as adaptive exposure techniques and iterative reconstruction, for radiation dose reduction.

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