A U-Net predicts spatially adaptive Total Variation weights from a filtered backprojection, yielding stable few-view CT reconstructions, though the supporting stability proof contains an error.
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Adaptive Weighted Total Variation boosted by learning techniques in few-view tomographic imaging
A U-Net predicts spatially adaptive Total Variation weights from a filtered backprojection, yielding stable few-view CT reconstructions, though the supporting stability proof contains an error.