CT image correction for beam hardening using simulated projection data

Meagher, J.M.; Mote, C. D.; Skinner, H.B.

doi:10.1109/23.55865

Cited by 39 publications

(16 citation statements)

References 9 publications

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“…The new algorithm is robust, also regarding its free parameters, the shape parameter η, and the number of basis images. Since sfEBHC does not require segmentation, because segmentation rather is replaced by a nonlinear operation on the image's gray scale, it may be useful in cases where most other known higher order beam hardening correction approaches, such as, 6,9,10,[15][16][17] for example, may not be applicable.…”

Section: Discussionmentioning

confidence: 99%

Segmentation‐free empirical beam hardening correction for CT

Schüller

Sawall

Stannigel³

et al. 2015

Medical Physics

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Section: Discussionmentioning

confidence: 99%

Segmentation‐free empirical beam hardening correction for CT

Schüller

Sawall

Stannigel³

et al. 2015

Medical Physics

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“…Despite the availability of sophisticated reconstruction algorithms, empirical corrections are arguably the most widely used class of beam hardening corrections. These can be applied prior to image reconstruction [20, 21], or applied to the reconstructed image by applying polynomial basis functions, linearization procedures, calibration curves, or conversion tables [22-26]. These empirical approaches have been used in laboratory desktop μCT systems with some success, but the polynomial corrections that were used were not perfect and could not completely remove beam hardening artifacts for all cases [27-30].…”

Section: Introductionmentioning

confidence: 99%

Beam hardening artifacts in micro-computed tomography scanning can be reduced by X-ray beam filtration and the resulting images can be used to accurately measure BMD

Meganck

Kozloff

Thornton

et al. 2009

Bone

161

130

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Bone mineral density (BMD) measurements are critical in many research studies investigating skeletal integrity. For preclinical research, micro-computed tomography (μCT) has become an essential tool in these studies. However, the ability to measure the BMD, directly from μCT images can be biased by artifacts such as beam hardening, in the image. This three-part study was designed to understand how the image acquisition process can affect the resulting BMD measurements and to verify that the BMD measurements are accurate. In the first part of this study, the effect of beam hardening-induced cupping artifacts on BMD measurements was examined. In the second part of this study, the number of bones in the X-ray path and the sampling process during scanning was examined. In the third part of this study, μCT-based BMD measurements were compared with ash weights to verify the accuracy of the measurements. The results indicate that beam hardening artifacts of up to 32.6% can occur in sample sizes of interest in studies investigating mineralized tissue and affect mineral density measurements. Beam filtration can be used to minimize these artifacts. The results also indicate that, for murine femora, the scan setup can impact densitometry measurements for both cortical and trabecular bone and morphologic measurements of trabecular bone. Last, when a scan setup that minimized all of these artifacts was used, the μCT based measurements correlated used well with ash weight measurements (R 2 = 0.983 when air was excluded), indicating that μCT can be an accurate tool for murine bone densitometry.

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“…13 Alternatively, the linearization for multiple material objects can be performed using an iterative post reconstruction (IPR) approach. 1,12,[14][15][16][17][18][19][20][21][22] IPR methods are initialized with a preliminary reconstruction of the data, which is used to estimate the intersection length of each material with each ray path. Using these material thicknesses and prior knowledge about the spectrum and materials, the sinogram can be corrected.…”

Section: Introductionmentioning

confidence: 99%