RTK/ImageQuality: Difference between revisions
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= Beam hardening = | = Beam hardening = | ||
* The acquired data may be linearized for a given material using [http://www.openrtk.org/Doxygen/classrtk_1_1LookupTableImageFilter.html rtk::LookupTableImageFilter]. There are several solutions to compute the lookup table: | * The acquired data may be linearized for a given material using [http://www.openrtk.org/Doxygen/classrtk_1_1LookupTableImageFilter.html rtk::LookupTableImageFilter] as explained, e.g., in Fig. 1 of [http://iopscience.iop.org/0031-9155/21/3/004 <nowiki>[Brooks and Di Chiro, PMB, 1976]</nowiki>]. There are several solutions to compute the lookup table: | ||
** Compute it from the knowledge of the spectrum of the x-ray source and the detector response, | ** Compute it from the knowledge of the spectrum of the x-ray source and the detector response, | ||
** Measure the attenuation for several thicknesses of the material of interest, | ** Measure the attenuation for several thicknesses of the material of interest, | ||
Revision as of 08:53, 5 August 2015
This page summarizes the existing and the future solutions in RTK for improving image quality of cone-beam (CB) CT images.
X-ray source imperfections
- Geometric blurring can be corrected by the scatter glare correction detailed in the detector imperfections section.
- Exposure fluctuations from projection to projection are common. They can be corrected by rtk::I0EstimationProjectionFilter which automatically estimates a weighting constant per projection using an histogram analysis. This filter only works if there are pixels in each projections that measure x-rays that traversed air only (except maybe a few projections using a revursive least-square . The filter does not have any parameter except the bitshift template value for the reduction of the histogram size. It is implemented for integer pixel types only.
- Focal spot motion cannot be corrected currently. It would require geometric calibration for each acquisition.
Detector imperfections
- Lag: the [ rtk::] filter implements correction implements
, see [Poludniowski et al, PMB, 2011] implemetend in [rtk::]
Beam hardening
- The acquired data may be linearized for a given material using rtk::LookupTableImageFilter as explained, e.g., in Fig. 1 of [Brooks and Di Chiro, PMB, 1976]. There are several solutions to compute the lookup table:
- Compute it from the knowledge of the spectrum of the x-ray source and the detector response,
- Measure the attenuation for several thicknesses of the material of interest,
- Do a tomography of a homogenous object (e.g., a cylinder), fix the lookup table the rtk::WaterPrecorrectionImageFilter] which implements [Kachelriess et al, Med Phys, 2006].
- Estimate the p and a parameters of equation 1 in [Ohnesorge et al, Eur Radiol, 1999]
- The algorithm of [Kyriakou et al, Med Phys, 2010 may easily be implemented from the existing code in RTK.
Truncated projection images
- The rtk::FFTRampImageFilter implements the heuristic solution of [Ohnesorge et al, Med Phys, 2000]. The parameter TruncationCorrection must be set.
- Exact reconstruction based differentiated backprojection and inverse Hilbert filtering (see, e.g., [Noo et al, PMB, 2004] is investigated in Lyon.