Empirical beam hardening correction (EBHC) for CT

Kyriakou, Yiannis; Meyer, Esther; Prell, Daniel; Kachelrieß, Marc

doi:10.1118/1.3477088

Cited by 137 publications

(158 citation statements)

References 30 publications

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“…Our empirical beam hardening correction (EBHC) uses the correction method as presented by Kyriakou et al 9 The main advantage of this beam hardening correction is the correction of beam hardening artifacts without any a priori-knowledge, ie, scan geometry, x-ray spectra, type of material, as compared with previously published beam hardening correction methods. [11][12][13] We adjusted the initial method in a way that suits the special needs when metallic implants are involved.…”

Section: Empirical Beam Hardening Correctionmentioning

confidence: 99%

“…Also, any soft-tissue segmentation algorithm can be applied to distinguish between different tissue classes, ie, the algorithms published in. 1,9 An important aspect of EBHC is that it simply corrects CT values in the image domain implying that image resolution remains unchanged because only offsets are added or subtracted from the original image. It was shown in previous publications that these simple postprocessing methods have minimal impact on spatial resolution.…”

Section: Empirical Minimizationmentioning

confidence: 99%

“…f 2 (r) forward projected yields the attenuation values p 2 corresponding to metal only. According to Kyriakou et al, 9 the attenuation values for the water-equivalent density can then be calculated as a series expansion of the original raw data p 0 and p 2 as…”

Section: Empirical Beam Hardening Correctionmentioning

confidence: 99%

“…9 The water-equivalent region is defined by simple thresholding of the initial volume with a higher and lower threshold T H and T L , respectively. T H ϭ 100 HU and T L ϭ Ϫ300 HU were set empirically throughout the correction process.…”

Section: Empirical Minimizationmentioning

confidence: 99%

“…Although in most cases the mandatory water precorrection corrects for respective inconsistencies in water-equivalent tissue, object mixtures such as bone and metal are not corrected. 1,9 Another important artifact source is the high quantum noise in the metal shadow in the raw data, caused by a low signal-to-noise ratio (SNR), which is amplified by the FBP reconstruction resulting in streak artifacts radiating from the implants. 10 Additionally, artifact sources such as scattered radiation, which causes a low SNR because of its high scatter-to-primary ratio, 1 or photon starvation, which may lead to high electronic noise, further add to the artifact characteristics.…”

mentioning

confidence: 99%

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Reducing Metal Artifacts in Computed Tomography Caused by Hip Endoprostheses Using a Physics-Based Approach

Prell

Kyriakou

Kachelrie

et al. 2010

Investigative Radiology

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Section: Empirical Beam Hardening Correctionmentioning

confidence: 99%

Section: Empirical Minimizationmentioning

confidence: 99%

Section: Empirical Beam Hardening Correctionmentioning

confidence: 99%

Section: Empirical Minimizationmentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Reducing Metal Artifacts in Computed Tomography Caused by Hip Endoprostheses Using a Physics-Based Approach

Prell

Kyriakou

Kachelrie

et al. 2010

Investigative Radiology

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Monte Carlo Approach for Estimating Density and Atomic Number From Dual‐Energy Computed Tomography Images of Carbonate Rocks

2017

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We develop a new Monte Carlo‐based inversion method for estimating electron density and effective atomic number from 3‐D dual‐energy computed tomography (CT) core scans. The method accounts for uncertainties in X‐ray attenuation coefficients resulting from the polychromatic nature of X‐ray beam sources of medical and industrial scanners, in addition to delivering uncertainty estimates of inversion products. Estimation of electron density and effective atomic number from CT core scans enables direct deterministic or statistical correlations with salient rock properties for improved petrophysical evaluation; this condition is specifically important in media such as vuggy carbonates where CT resolution better captures core heterogeneity that dominates fluid flow properties. Verification tests of the inversion method performed on a set of highly heterogeneous carbonate cores yield very good agreement with in situ borehole measurements of density and photoelectric factor.

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Characterization of size‐specific effects during dual‐energy CT material decomposition of non‐iodine materials

Miller

DiMaso

Huang-Vredevoogd

et al. 2021

J Applied Clin Med Phys

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The dual-energy CT (DECT) LiverVNC application class in the Siemens Syngo.via software has been used to perform non-iodine material decompositions. However, the LiverVNC application is designed with an optional size-specific calibration based on iodine measurements. This work investigates the effects of this iodine-based size-specific calibration on non-iodine material decomposition and benchmarks alternative methods for size-specific calibrations. Methods: Calcium quantification was performed with split-filter and sequentialscanning DECT techniques on the Siemens SOMATOM Definition Edge CT scanner. Images were acquired of the Gammex MECT abdomen and head phantom containing calcium inserts with concentrations ranging from 50-300 mgCa/ml. Several workflows were explored investigating the effects of sizespecific dual-energy ratios (DERs) and the beam hardening correction (BHC) function in the LiverVNC application. Effects of image noise were also investigated by varying CTDI vol and using iterative reconstruction (ADMIRE). Results: With the default BHC activated, Syngo.via underestimated the calcium concentrations in the abdomen for sequential-scanning acquisitions, leaving residual calcium in the virtual non-contrast images and underestimating calcium in the enhancement images for all DERs. Activation of the BHC with split-filter images resulted in a calcium over-or underestimation depending on the DER. With the BHC inactivated, the use of a single DER led to an under-or overestimate of calcium concentration depending on phantom size and DECT modality. Optimal results were found with BHC inactivated using size-specific DERs. CTDI vol levels and ADMIRE had no significant effect on results. Conclusion: When performing non-iodine material decomposition in the Liv-erVNC application class, it is important to understand the implications of the BHC function and to account for patient size appropriately. The BHC in the Liv-erVNC application is specific to iodine and leads to inaccurate quantification of other materials. The inaccuracies can be overcome by deactivating the BHC function and using size-specific DERs, which provided the most accurate calcium quantification.

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Empirical beam hardening correction (EBHC) for CT

Cited by 137 publications

References 30 publications

Reducing Metal Artifacts in Computed Tomography Caused by Hip Endoprostheses Using a Physics-Based Approach

Reducing Metal Artifacts in Computed Tomography Caused by Hip Endoprostheses Using a Physics-Based Approach

Monte Carlo Approach for Estimating Density and Atomic Number From Dual‐Energy Computed Tomography Images of Carbonate Rocks

Characterization of size‐specific effects during dual‐energy CT material decomposition of non‐iodine materials

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