Scatter correction using a primary modulator on a clinical angiography C-arm CT system

A novel beam stopper-based approach for scatter correction in digital planar radiography

X-ray scatter in planar radiography degrades the contrast resolution of the image, thus reducing its diagnostic utility. Antiscatter grids partially block scattered photons at the cost of increasing the dose delivered by two- to four-fold and posing geometrical restrictions that hinder their use for other acquisition settings, such as portable radiography. The few software-based approaches investigated for planar radiography mainly estimate the scatter map from a low-frequency version of the image. We present a novel method for scatter correction in planar imaging based on direct patient measurements. Samples from the shadowed regions of an additional partially obstructed projection acquired with a beam stopper placed between the X-ray source and the patient are used to estimate the scatter map. Evaluation with simulated and real data showed an increase in contrast resolution for both lung and spine and recovery of ground truth values superior to those of three recently proposed methods. Our method avoids the biases of post-processing methods and yields results similar to those for an antiscatter grid while removing geometrical restrictions at around half the radiation dose. It can be used in unconventional imaging techniques, such as portable radiography, where training datasets needed for deep-learning approaches would be very difficult to obtain.

X-Ray Scatter Estimation Using Deep Splines

X-ray scatter compensation is a very desirable technique in flat-panel X-ray imaging and cone-beam computed tomography. State-of-the-art U-net based scatter removal approaches yielded promising results. However, as there are no physics' constraints applied to the output of the U-Net, it cannot be ruled out that it yields spurious results. Unfortunately, in the context of medical imaging, those may be misleading and could lead to wrong conclusions. To overcome this problem, we propose to embed B-splines as a known operator into neural networks. This inherently constrains their predictions to well-behaved and smooth functions. In a study using synthetic head and thorax data as well as real thorax phantom data, we found that our approach performed on par with U-net when comparing both algorithms based on quantitative performance metrics. However, our approach not only reduces runtime and parameter complexity, but we also found it much more robust to unseen noise levels. While the U-net responded with visible artifacts, the proposed approach preserved the X-ray signal's frequency characteristics.

A phantom study on dose efficiency for orthopedic applications: Comparing slot-scanning radiography using ultra-small-angle tomosynthesis to conventional radiography

PURPOSE

This paper studies the abilities of a twin-robotic x-ray slot-scanning system for orthopedic imaging to reduce dose by scatter rejection compared to conventional digital radiography.

METHODS

We investigate the dose saving capabilities, especially in terms of the signal- and the contrast-to-noise ratio, as well as the scatter-to-primary ratio of the proposed slot-scanning method in comparison to the state-of-the-art method for length-extended imaging. As a baseline, we use x-ray parameters of two clinically established acquisition protocols that provide the same detector entrance dose but are profoundly different in patient dose. To obtain an estimate of the photon-related noise directly from an x-ray image, we implement a Poisson-Gaussian noise model. This model is used to compare the dose efficiency of two settings and combined with the well-known K SNR to determine the transmission parameters. We present a method with an associated measurement protocol, utilizing the robotic capabilities of the used system to automatically obtain quasi-scatter-free ground-truth data with exact geometric correspondence to full-field and slot acquisitions. In total, we investigate two body regions (thoracic spine and lumbar spine) in anterior-posterior view with two patient sizes (BMI = 22 and 30) in two acquisition modes (conventional and slot scan with a flat-panel detector) with and without anti-scatter grid using an anthropomorphic upper-body phantom.

RESULTS

We have shown that it is feasible to combine the proposed approach with the K SNR for the determination of scatter rejection parameters. The use of an anti-scatter grid is indicated for full-field acquisitions allowing for dose savings up to 46% compared to their gridless counterparts. When changing the acquisition mode to the investigated slot scan, the use of an anti-scatter grid has no major impact on the image quality in terms of dose efficiency, in particular for patients with a BMI of 22. However, an increased contrast improvement factor was found. For normal-sized patients, up to 53% of dose can be saved additionally in comparison to full-field acquisitions with grid. Moreover, we could demonstrate that a slot size of 5 cm and air gap of 10 cm is sufficient to achieve scatter-to-primary ratios, which are equal or better compared to those of the full-field acquisitions with a grid.

CONCLUSIONS

We have shown, that the slot-scanning approach is always superior to the conventional full-field acquisition in terms of signal-to-noise and scatter-to-primary ratios. Compared to the state-of-the-art acquisition protocols with a grid, dose savings up to 53% are possible due to the scatter rejection without compromising the SNR. Hence, the use of the slot-scanning method is indicated, especially when it comes to regularly carried-out follow-up acquisitions, for example, in the case of scoliosis monitoring.

An analysis of scatter characteristics in x-ray CT spectral correction

X-ray scatter remains a major physics challenge in volumetric computed tomography (CT), whose physical and statistical behaviors have been commonly leveraged in order to eliminate its impact on CT image quality. In this work, we conduct an in-depth derivation of how the scatter distribution and scatter to primary ratio (SPR) will change during the spectral correction, leading to an interesting finding on the property of scatter. Such a characterization of scatter's behavior provides an analytic approach of compensating for the SPR as well as approximating the change of scatter distribution after spectral correction, even though both of them might be significantly distorted as the linearization mapping function in spectral correction could vary a lot from one detector pixel to another. We conduct an evaluation of SPR compensations on a Catphan phantom and an anthropomorphic chest phantom to validate the characteristics of scatter. In addition, this scatter property is also directly adopted into CT imaging using a spectral modulator with flying focal spot technology (SMFFS) as an example to demonstrate its potential in practical applications. For cone-beam CT scans at both 80 and 120 kVp, CT images with accurate CT numbers can be achieved after spectral correction followed by the appropriate SPR compensation based on our presented scatter property. In the case of the SMFFS based cone-beam CT scan of the Catphan phantom at 120 kVp, after a scatter correction using an analytic algorithm derived from the scatter property, CT image quality was significantly improved, with the averaged root mean square error reduced from 297.9 to 6.5 Hounsfield units (HU).

Scatter Correction for Spectral CT Using a Primary Modulator Mask

The problem of scattered radiation correction in computed tomography (CT) is well known because scatter induces a bias, a loss of contrast and artifacts. Numerous strategies have been proposed in conventional CT (using energy-integrating detectors) but the problem is still open in the field of spectral CT, a new imaging technique based on energy-selective photon counting detectors. The aim of the present study is to introduce a scatter correction method adapted to multi-energy imaging and based on the use of a primary modulator mask. The main contributions are a correction matrix, which compensates for the effect of the mask, a scatter model based on B-splines and a cost function based on the mask structures and robust to the object structures. The performances of the method have been evaluated on both simulated and experimental data. The mean relative error was reduced from 20% in the lower energy-bins without correction to 4% with the proposed technique, which is close to the error caused by statistical noise.

Reduction of beam hardening artifacts on real C-arm CT data using polychromatic statistical image reconstruction

PURPOSE

This work aims at the compensation of beam hardening artifacts by the means of an extended three-dimensional polychromatic statistical reconstruction to be applied for flat panel cone-beam CT.

METHODS

We implemented this reconstruction technique as being introduced by Elbakri et al. (2002) [1] for a multi-GPU system, assuming the underlying object consists of several well-defined materials. Furthermore, we assume one voxel can only contain an overlap of at most two materials, depending on its density value. Given the X-ray spectrum, the procedure enables to reconstruct the energy-dependent attenuation values of the volume.

RESULTS

We evaluated the method by using flat-panel cone-beam CT measurements of structures containing small metal objects and clinical head scan data. In comparison with the water-corrected filtered backprojection, as well as a maximum likelihood reconstruction with a consistency-based beam hardening correction, our method features clearly reduced beam hardening artifacts and a more accurate shape of metal objects.

CONCLUSIONS

Our multi-GPU implementation of the polychromatic reconstruction, which does not require any image pre-segmentation, clearly outperforms the standard reconstructions of objects, with respect to beam hardening even in the presence of metal objects inside the volume. However, remaining artifacts, caused mainly by the limited dynamic range of the detector, may have to be addressed in future work.

Physics-based spectral compensation algorithm for x-ray CT with primary modulator

X-ray computed tomography (CT) scatter correction using primary modulator has been continuously developed over the past years, with progress in improving the performance of scatter correction. In this work, we further advance the primary modulator technique towards practical applications where the spectral nonuniformity caused by the modulator continues to be a challenging problem. A physics-based spectral compensation algorithm is proposed to adaptively correct for the spectral nonuniformity, and hence to reduce the resultant ring artifacts on reconstructed CT images. First, an initial spectrum of the CT system without the primary modulator is modeled using an understanding of x-ray CT physics, and optimized by an expectation maximization method; then, the optimized estimation of the initial spectrum is utilized to adaptively calculate the effective modulator thickness from measured transmissions of the primary modulator at each detector element, leading to a set of new spectra that is able to capture the nonuniform spectral distribution of the primary modulator; finally, using the modulator-modeled spectrum, a beam hardening mapping function is generated and beam hardening correction is applied to CT projections. A CatPhan600 phantom and an anthropomorphic thorax phantom were scanned with three different primary modulators to evaluate the approach. For the Catphan phantom, the spectral compensation algorithm efficiently removes the ring (and band) artifacts that otherwise dominate the reconstructed CT image. For the three modulators with nominal copper thickness of 52.5, 105 and 210 [Formula: see text]m, our method reduces the CT number nonuniformity from 147.9, 436.2 and 696.4 Hounsfield units (HU) to 14.6, 26.2 and 13.6 HU, respectively, close to that of the reference image (i.e. 7.5 HU). For the thorax phantom, the ring artifacts are also suppressed significantly on the transaxial image; on the sagittal image, the alternating black-and-white patterns are largely removed, with the CT number nonuniformity being reduced from 282.0 HU to 38.5 HU.

Virtual scatter modulation for X-ray CT scatter correction using primary modulator

A new scatter estimation algorithm with a concept of virtual scatter modulation for X-ray scatter correction using primary modulator is proposed to reduce the aliasing errors in the estimated scatter. Virtual scatter modulation can be realized through dividing the measured primary-modulated image by the measured modulation function. After the division, the aggravation of the aliasing of primary due to the non-uniformity of the modulation function is largely transferred to that of scatter. Since scatter in general has less high frequencies than primary does, the aggravation of its aliasing is expected to be weaker, and therefore the overall aliasing can be reduced. A CatPhan©600 phantom and an anthropomorphic thorax phantom are scanned on a tabletop X-ray cone-beam computed tomography system to validate our proposed algorithm. On the Catphan phantom, the oscillations that are clearly observed in the central region of the Catphan scatter profile estimated using the original primary-modulation algorithm, are mostly eliminated with the proposed scatter modulation algorithm, leading to less residual artifacts and better CT number uniformity in the reconstructed image. Compared with 38.9 HU of CT nonuniformity in a selected uniform region when the primary-modulation algorithm is used, the new algorithm significantly reduces it to 4.5 HU, reaching the same level of uniformity as the ground truth reference. On the thorax phantom, overall better CT number uniformity is also achieved.