Deep bowtie and patient scatter correction applied to clinical photon-counting CT

In addition to the objects or patients that are scanned in a CT, other components in the beam path can also cause scatter. In particular, scatter by the bowtie filter, which is typically the last filter before the patient, can create image artifacts, impair contrast and considerably distort the CT values. Previous studies have shown that deep convolutional neural networks are very effective correcting scattered photons in clinical CTs. In this work, we present an adapted approach of the deep scatter estimation (DSE) method for photon-counting (PC) CT that effectively corrects both object and bowtie scatter. Our best network reduces the mean absolute error of object and bowtie scatter from 8.1 HU to 0.9 HU.