Bärbel Kratz

A fully 3D approach for metal artifact reduction in computed tomography

PURPOSE In computed tomography imaging metal objects in the region of interest introduce inconsistencies during data acquisition. Reconstructing these data leads to an image in spatial domain including star-shaped or stripe-like artifacts. In order to enhance the quality of the resulting image the influence of the metal objects can be reduced. Here, a metal artifact reduction (MAR) approach is proposed that is based on a recomputation of the inconsistent projection data using a fully three-dimensional Fourier-based interpolation. The success of the projection space restoration depends sensitively on a sensible continuation of neighboring structures into the recomputed area. Fortunately, structural information of the entire data is inherently included in the Fourier space of the data. This can be used for a reasonable recomputation of the inconsistent projection data. METHODS The key step of the proposed MAR strategy is the recomputation of the inconsistent projection data based on an interpolation using nonequispaced fast Fourier transforms (NFFT). The NFFT interpolation can be applied in arbitrary dimension. The approach overcomes the problem of adequate neighborhood definitions on irregular grids, since this is inherently given through the usage of higher dimensional Fourier transforms. Here, applications up to the third interpolation dimension are presented and validated. Furthermore, prior knowledge may be included by an appropriate damping of the transform during the interpolation step. This MAR method is applicable on each angular view of a detector row, on two-dimensional projection data as well as on three-dimensional projection data, e.g., a set of sequential acquisitions at different spatial positions, projection data of a spiral acquisition, or cone-beam projection data. RESULTS Results of the novel MAR scheme based on one-, two-, and three-dimensional NFFT interpolations are presented. All results are compared in projection data space and spatial domain with the well-known one-dimensional linear interpolation strategy. CONCLUSIONS In conclusion, it is recommended to include as much spatial information into the recomputation step as possible. This is realized by increasing the dimension of the NFFT. The resulting image quality can be enhanced considerably.

Reference‐free ground truth metric for metal artifact evaluation in CT images

PURPOSE In computed tomography (CT), metal objects in the region of interest introduce data inconsistencies during acquisition. Reconstructing these data results in an image with star shaped artifacts induced by the metal inconsistencies. To enhance image quality, the influence of the metal objects can be reduced by different metal artifact reduction (MAR) strategies. For an adequate evaluation of new MAR approaches a ground truth reference data set is needed. In technical evaluations, where phantoms can be measured with and without metal inserts, ground truth data can easily be obtained by a second reference data acquisition. Obviously, this is not possible for clinical data. Here, an alternative evaluation method is presented without the need of an additionally acquired reference data set. METHODS The proposed metric is based on an inherent ground truth for metal artifacts as well as MAR methods comparison, where no reference information in terms of a second acquisition is needed. The method is based on the forward projection of a reconstructed image, which is compared to the actually measured projection data. RESULTS The new evaluation technique is performed on phantom and on clinical CT data with and without MAR. The metric results are then compared with methods using a reference data set as well as an expert-based classification. It is shown that the new approach is an adequate quantification technique for artifact strength in reconstructed metal or MAR CT images. CONCLUSIONS The presented method works solely on the original projection data itself, which yields some advantages compared to distance measures in image domain using two data sets. Beside this, no parameters have to be manually chosen. The new metric is a useful evaluation alternative when no reference data are available.

Metal artifact reduction in computed tomography using nonequispaced fourier transform

Metal objects in the field of view of a computed tomography (CT) scanner cause several artifacts inside the reconstructed image. By reducing the influence of these metallic objects the image quality can be enhanced. We propose a metal artifact reduction (MAR) method based on interpolation using Nonequispaced Fast Fourier Transforms (NFFT). By damping the transformation additional a priori knowledge may be included during the interpolation step. The results are reconstructed with a weighted maximum likelihood expectation maximization algorithm (¿-MLEM) and finally compared to two common one dimensional polynomial interpolation methods.

Non-equispaced Fourier Transform Vs. Polynomial-Based Metal Artifact Reduction in Computed Tomography

We propose a method, which treats metal artifact reduction in CT by sinogram restoration as a problem of scattered data interpolation. Corrupted sinogram entries are discarded and replaced with artificially generated values. The presented interpolation algorithm is based on the 2D non-equispaced fast Fourier transform (NFFT). Results are compared to two common polynomial interpolation schemes.

Influence of metal segmentation on the quality of metal artifact reduction methods

In computed tomography, star shape artifacts are introduced by metal objects, which are inside a patients body. The quality of the reconstructed image can be enhanced by applying a metal artifact reduction method. Unfortunately, a method that removes all such artifacts in order to make the images valuable for medical diagnosis remains to be found. In this study, the influence of metal segmentation is investigated. A thresholding technique, which is the state of the art in the field, is compared with a manual segmentation. Results indicate that a more accurate segmentation can lead to a preservation of important anatomical details, which are of high value for medical diagnosis.

On Limitations of 1D Interpolation-Based Metal Artefact Reduction Approaches – A Comparison of FBP versus MLEM

In computed tomography (CT) metal objects cause nonlinear variations of the acquired Radon data. During image reconstruction the inconsistencies introduce star shaped artefacts around the metal objects extending over the entire image. Due to this data deterioration, the acquired image is often unusable for diagnostic assistance or, at worst, causes a false diagnosis.

Quality evaluation for metal influenced CT data

In Computed Tomography (CT) metal objects in the region of interest introduce data inconsistencies during acquisition. The reconstruction process results in an image with star shaped artifacts. To enhance image quality the influence of metal objects can be reduced by different metal artifact reduction (MAR) strategies. For an adequate evaluation of new MAR approaches a ground truth reference data set is needed. In technical evaluations, where phantoms are available with and without metal inserts, ground truth data can easily be acquired by a reference scan. Obviously, this is not possible for clinical data. In this work, three different evaluation methods for metal artifacts as well as comparison of MAR methods without the need of an acquired reference data set will be presented and compared. The first metric is based on image contrast; a second approach involves the filtered gradient information of the image, and the third method uses a forward projection of the reconstructed image followed by a comparison with the actually measured projection data. All evaluation techniques are performed on phantom and on clinical CT data with and without MAR and compared with reference-based evaluation methods as well as expert-based classifications.

Modified Eulers Elastica Inpainting for Metal Artifact Reduction in CT

In computed tomography (CT) metal causes strong streak artifacts in the reconstructed images, which may hinder the correct diagnosis of patients. In this work, metal artifacts are reduced using the modified Eulers elastica and curvature based sinogram inpainting (EECSI). The inconsistent data is deleted from the sinogram and replaced by a two-dimensional interpolation strategy based on the surrounding data information using partial differential equations. The inpainting domain is defined by a binary mask that is calculated using a thresholding method in the preliminary reconstructed image with a following forward projection of the metal-only image. Here, the EECSI is modified by a statistic weighting function that regulates the time step size depending on the probability of a gray value. Additionally, the connectivity principle is strengthened by applying a different strategy in the numerical implementation compared to prior methods. The measurements are realized on a Philips Tomoscan M/EG scanner using a torso phantom with the physical properties of an average male torso, suitable for medical experiments. For evaluation, the results are compared to the ones achieved by using the original EECSI and the classically used one-dimensional linear interpolation method. It is demonstrated that the performed modifications result in a better metal artifact suppression.

Referenzlose Qualitätsbestimmung von CT-Bildern

In der Computertomographie konnen metallische Objekte oder Bewegungen durch Patienten zu Inkonsistenzen innerhalb der Projektionswerte fuhren. Bei der anschliesenden Rekonstruktion der tomographischen Schnittbilder kommt es durch diese inkonsistenten Daten zu Artefakten, welche die diagnostische Aussagekraft des Bildes beeinflussen konnen. In diesem Beitrag wird die Anwendbarkeit zweier referenzloser Metriken fur die Beurteilung der Bildqualitat in der Computertomographie uberpruft. Die beiden Metriken basieren auf der Verwendung des Just-Noticeable-Blur (JNB)-Prinzips und wurden als wahrnehmungsbasierte Scharfemetriken entwickelt, um die Unscharfe in Bildern unterschiedlichen Inhaltes zu beurteilen. Es wird gezeigt, dass eine der Varianten fur die Beurteilung von Bewegungsartefakten und die andere fur Metallartefakte verwendet werden kann.