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Correction for patient table‐induced scattered radiation in cone‐beam computed tomography (CBCT)
Author(s) -
Sun Mingshan,
Nagy Tamás,
Virshup Gary,
Partain Larry,
Oelhafen Markus,
StarLack Josh
Publication year - 2011
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3557468
Subject(s) - imaging phantom , cone beam computed tomography , isocenter , optics , monte carlo method , physics , artifact (error) , computer science , image guided radiation therapy , iterative reconstruction , computer vision , projection (relational algebra) , superposition principle , medical imaging , artificial intelligence , algorithm , computed tomography , mathematics , medicine , statistics , radiology , quantum mechanics
Purpose: In image‐guided radiotherapy, an artifact typically seen in axial slices of x‐ray cone‐beam computed tomography (CBCT) reconstructions is a dark region or “black hole” situated below the scan isocenter. The authors trace the cause of the artifact to scattered radiation produced by radiotherapy patient tabletops and show it is linked to the use of the offset‐detector acquisition mode to enlarge the imaging field‐of‐view. The authors present a hybrid scatter kernel superposition (SKS) algorithm to correct for scatter from both the object‐of‐interest and the tabletop.Methods: Monte Carlo simulations and phantom experiments were first performed to identify the source of the black hole artifact. For correction, a SKS algorithm was developed that uses separate kernels to estimate scatter from the patient tabletop and the object‐of‐interest. Each projection is divided into two regions, one defined by the shadow cast by the tabletop on the imager and one defined by the unshadowed region. The region not shadowed by the tabletop is processed using the recently developed fast adaptive scatter kernel superposition (fASKS) method which employs asymmetric kernels that best model scatter transport through bodylike objects. The shadowed region is convolved with a combination of slab‐derived symmetric SKS kernels and asymmetric fASKS kernels. The composition of the hybrid kernels is projection‐angle‐dependent. To test the algorithm, pelvis phantom and in vivo data were acquired using a CBCT test stand, a Varian Acuity simulator, and a Varian On‐Board Imager, all of which have similar geometries and components. Artifact intensities and Hounsfield unit (HU) accuracies in the reconstructions were assessed before and after the correction.Results: The hybrid kernel algorithm provided effective correction and produced substantially better scatter estimates than the symmetric SKS or asymmetric fASKS methods alone. HU nonuniformities in the reconstructed pelvis phantom were reduced from 220 to 50 HU (i.e., 22%–5%). In the in vivo scans, the black hole artifact was reduced by up to 147 HU, a 73% improvement, and anatomical details in the prostate and rectum areas were made considerably more visible.Conclusions: Radiotherapy tabletops, which are generally flatter and larger than those used for diagnostic CT, can produce significant scatter‐related artifacts. The proposed hybrid SKS algorithm accurately estimates scatter from both the object‐of‐interest and the patient tabletop, and resulting image uniformities and HU accuracies are greatly improved.