Blind deconvolution for blocker-based scatter correction of CBCT

Among numerous scatter correction (SC) methods of cone-beam computed tomography (CBCT), the use of lead-strip blockers is low-cost and easy to implement and holds potential to significantly lower patient radiation dose. In blocker-based SC methods, the signal detected in the blocked region is deemed scatter through an ideal projection assumption and used to estimate scatter in the unblocked region. However, since the signal in the blocked region is not pure scatter, meticulous adjustment of working parameters has to be done to avoid over- and under-correction of scatter. In this work, we propose to model blocked-based CBCT projections as ideal projections convolved by a point spread function and to use a blind deconvolution method to recover true scatter in blocked regions. Combined with blockers' motion and statistical iterative reconstruction, the proposed method can yield better image quality and more accurate CT numbers, as demonstrated by physical phantom data.