Improved scatter correction using adaptive scatter kernel superposition
- 28 October 2010
- journal article
- Published by IOP Publishing in Physics in Medicine & Biology
- Vol. 55 (22), 6695-6720
- https://doi.org/10.1088/0031-9155/55/22/007
Abstract
Accurate scatter correction is required to produce high-quality reconstructions of x-ray cone-beam computed tomography (CBCT) scans. This paper describes new scatter kernel superposition (SKS) algorithms for deconvolving scatter from projection data. The algorithms are designed to improve upon the conventional approach whose accuracy is limited by the use of symmetric kernels that characterize the scatter properties of uniform slabs. To model scatter transport in more realistic objects, nonstationary kernels, whose shapes adapt to local thickness variations in the projection data, are proposed. Two methods are introduced: (1) adaptive scatter kernel superposition (ASKS) requiring spatial domain convolutions and (2) fast adaptive scatter kernel superposition (fASKS) where, through a linearity approximation, convolution is efficiently performed in Fourier space. The conventional SKS algorithm, ASKS, and fASKS, were tested with Monte Carlo simulations and with phantom data acquired on a table-top CBCT system matching the Varian On-Board Imager (OBI). All three models accounted for scatter point-spread broadening due to object thickening, object edge effects, detector scatter properties and an anti-scatter grid. Hounsfield unit (HU) errors in reconstructions of a large pelvis phantom with a measured maximum scatter-to-primary ratio over 200% were reduced from -90 ± 58 HU (mean ± standard deviation) with no scatter correction to 53 ± 82 HU with SKS, to 19 ± 25 HU with fASKS and to 13 ± 21 HU with ASKS. HU accuracies and measured contrast were similarly improved in reconstructions of a body-sized elliptical Catphan phantom. The results show that the adaptive SKS methods offer significant advantages over the conventional scatter deconvolution technique.Keywords
This publication has 33 references indexed in Scilit:
- The influence of bowtie filtration on cone‐beam CT image qualityMedical Physics, 2008
- Scatter kernel estimation with an edge-spread function method for cone-beam computed tomography imagingPhysics in Medicine & Biology, 2008
- Efficiency of antiscatter grids for flat-detector CTPhysics in Medicine & Biology, 2007
- SU-FF-I-22: Scatter Correction for Flat Detector Cone-Beam CT Based On Simulated Sphere ModelsMedical Physics, 2007
- Advances in Image-Guided Radiation TherapyJournal of Clinical Oncology, 2007
- Intraoperative cone‐beam CT for guidance of head and neck surgery: Assessment of dose and image quality using a C‐arm prototypeMedical Physics, 2006
- Combining deterministic and Monte Carlo calculations for fast estimation of scatter intensities in CTPhysics in Medicine & Biology, 2006
- Accelerated Simulation of Cone Beam X-Ray Scatter ProjectionsIEEE Transactions on Medical Imaging, 2004
- Scatter estimation for a digital radiographic system using convolution filteringMedical Physics, 1987
- Practical cone-beam algorithmJournal of the Optical Society of America A, 1984