A general CT reconstruction algorithm for model-based material decomposition

Tilley, Steven; Zbijewski, Wojciech; Siewerdsen, Jeffrey H.; Stayman, J. Webster

doi:10.1117/12.2293776

Cited by 10 publications

(12 citation statements)

References 20 publications

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“…This suggests that MBMD may be used with other non-traditional acquisition protocols such as unconventional filtration (Yu et al 2016, Xi et al 2017, Stayman and Tilley 2018, multiple limited angle scans (Chen et al 2017) and systems with multiple axially oriented x-ray sources (Gang et al 2018). Related work has applied the MBMD approach to kV-switching (Tilley et al 2018b) and x-ray beam spectral filtering (Stayman and Tilley 2018) scenarios. These studies further support the robustness of this approach, demonstrating its application in additional acquisition strategies.…”

Section: Discussionmentioning

confidence: 99%

Model-based material decomposition with a penalized nonlinear least-squares CT reconstruction algorithm

2019

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Spectral information in CT maybe used for material decomposition to produce accurate reconstructions of material density and to separate materials with similar overall attenuation. Traditional methods separate the reconstruction and decomposition steps, often resulting in undesirable trade-offs (e.g. sampling constraints, a simplified spectral model). In this work, we present a model-based material decomposition algorithm which performs the reconstruction and decomposition simultaneously using a multienergy forward model. In a kV-switching simulation study, the presented method is capable of reconstructing iodine at 0.5 mg ml −1 with a contrast-tonoise ratio greater than two, as compared to 3.0 mg ml −1 for image domain decomposition. The presented method also enables novel acquisition methods, which was demonstrated in this work with a combined kV-switching/split-filter acquisition explored in simulation and physical test bench studies. This novel design used four spectral channels to decompose three materials: water, iodine, and gadolinium. In simulation, the presented method accurately reconstructed concentration value estimates with RMSE values of 4.86 mg ml −1 for water, 0.108 mg ml −1 for iodine and 0.170 mg ml −1 for gadolinium. In test-bench data, the RMSE values were 134 mg ml −1 ,5.26 mg ml −1 and 1.85 mg ml −1 , respectively. These studies demonstrate the ability of modelbased material decomposition to produce accurate concentration estimates in challenging spatial/ spectral sampling acquisitions.

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Section: Discussionmentioning

confidence: 99%

Model-based material decomposition with a penalized nonlinear least-squares CT reconstruction algorithm

2019

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“…50 mg/mL) and the maximum water concentration (i.e. 1,000 mg/mL) in the phantom 5 . Detector pixels were binned by 6 × 6 during projection postprocessing before reconstructions.…”

Section: Simulation Studymentioning

confidence: 98%

“…m {k} (ε) is the energy-dependent mass-attenuation coefficient of the base material k, and ρ {k} is the unknown local density (concentration). We have shown that this forward model can be written in a general matrix form 5 :…”

Section: Known-component Model-based Materials Decomposition (Kc-mbmd)mentioning

confidence: 99%

“…Assuming that the measurement y follows Gaussian distribution with mean ȳ and covariance Ky, the representation in Eq. 2 permits the use of a previously developed generalized nonlinear PWLS algorithm with the following objective function 5,7 :…”

Section: Known-component Model-based Materials Decomposition (Kc-mbmd)mentioning

confidence: 99%

“…We have recently proposed a model-based algorithm for simultaneous DE reconstruction and material decomposition (i.e. Model-Based Material Decomposition, MBMD) 5 . The algorithm can perform decompositions directly from the projections, but, unlike conventional methods, does not require matching LE and HE ray paths.…”

Section: Introductionmentioning

confidence: 99%

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Known-component model-based material decomposition for dual energy imaging of bone compositions in the presence of metal implant

Liu

Tilley

Cao

et al. 2019

15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine

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Dual energy computed tomography (DE CT) is a promising technology for the assessment of bone compositions. One of potential applications involves evaluations of fracture healing using longitudinal measurements of callus mineralization. However, imaging of fractures is often challenged by the presence of metal fixation hardware. In this work, we report on a new simultaneous DE reconstruction-decomposition algorithm that integrates the previously introduced Model-Based Material Decomposition (MBMD) with a Known-Component (KC) framework to mitigate metal artifacts. The algorithm was applied to the DE data obtained on a dedicated extremity cone-beam CT (CBCT) with capability for weight-bearing imaging. To acquire DE projections in a single gantry rotation, we exploited a unique multisource design of the system, where three X-ray sources were mounted parallel to the axis of rotation. The central source provided high energy (HE) data at 120 kVp, while the two remaining sources were operated at a low energy (LE) of 60 kVp. This novel acquisition trajectory further motivates the use of MBMD to accommodate this complex DE sampling pattern. The algorithm was validated in a simulation study using a digital extremity phantom. The phantom consisted of a water background with an insert containing varying concentrations of calcium (50-175 mg/mL). Two configurations of titanium implants were considered: a fixation plate and an intramedullary nail. The accuracy of calcium-water decompositions obtained with the proposed KC-MBMD algorithm was compared to MBMD without metal component model. Metal artifacts were almost completely removed by KC-MBMD. Relative absolute errors of calcium concentration in the vicinity of metal were 6%-31% for KC-MBMD (depending on the calcium insert and implant configuration), compared favorably to 48%-273% for MBMD. Moreover, accuracy of concentration estimates for KC-MBMD in the presence of metal implant approached that of MBMD in a configuration without implant (6%-23%). The proposed algorithm achieved accurate DE material decomposition in the presence of metal implants using a non-conventional, axial multisource DE acquisition pattern.

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Densely sampled spectral modulation for x‐ray CT using a stationary modulator with flying focal spot: a conceptual and feasibility study of scatter and spectral correction

et al. 2021

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Modulation of the x-ray source in computed tomography (CT) by a designated filter to achieve a desired distribution of photon flux has been greatly advanced in recent years. In this work, we present a densely sampled spectral modulation (DSSM) as a promising low-cost solution to quantitative CT imaging in the presence of scatter. By leveraging a special stationary filter (namely a spectral modulator) and a flying focal spot, DSSM features a strong correlation in the scatter distributions across focal spot positions and sees no substantial projection sparsity or misalignment in data sampling, making it possible to simultaneously correct for scatter and spectral effects in a unified framework. Methods: The concept of DSSM is first introduced, followed by an analysis of the design and benefits of using the stationary spectral modulator with a flying focal spot (SMFFS) that dramatically changes the data sampling and its associated data processing. With an assumption that the scatter distributions across focal spot positions have strong correlation, a scatter estimation and spectral correction algorithm from DSSM is then developed, where a dual-energy modulator along with two flying focal spot positions is of interest. Finally, a phantom study on a tabletop cone-beam CT system is conducted to understand the feasibility of DSSM by SMFFS, using a copper modulator and by moving the x-ray tube position in the X direction to mimic the flying focal spot. Results: Based on our analytical analysis of the DSSM by SMFFS, the misalignment of low-and high-energy projection rays can be reduced by a factor of more than 10 when compared with a stationary modulator only. With respect to modulator design, metal materials such as copper, molybdenum, silver, and tin could be good candidates in terms of energy separation at a given attenuation of photon flux. Physical experiments using a Catphan phantom as well as an anthropomorphic chest phantom demonstrate the effectiveness of DSSM by SMFFS with much better CT number accuracy and less image artifacts. The root mean squared error was reduced from 297.9 to 6.5 Hounsfield units (HU) for the Catphan phantom and from 409.3 to 39.2 HU for the chest phantom. Conclusions: The concept of DSSM using a SMFFS is proposed. Phantom results on its scatter estimation and spectral correction performance validate our main ideas and key assumptions, demonstrating its potential and feasibility for quantitative CT imaging.

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A general CT reconstruction algorithm for model-based material decomposition

Cited by 10 publications

References 20 publications

Model-based material decomposition with a penalized nonlinear least-squares CT reconstruction algorithm

Model-based material decomposition with a penalized nonlinear least-squares CT reconstruction algorithm

Known-component model-based material decomposition for dual energy imaging of bone compositions in the presence of metal implant

Densely sampled spectral modulation for x‐ray CT using a stationary modulator with flying focal spot: a conceptual and feasibility study of scatter and spectral correction

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