Metal Artefact Reduction
One of the biggest challenges in the field of Computed Tomography is the presence of metal objects such as hip implants, artificial joints, pacemaker, or orthopedic screws within a patient's body. Caused by the extremely high attenuation coefficients and the physical characteristics of x-ray photons one can obtain severe streaking artefacts in the reconstructed image. The obtained artefacts reduce the diagnostic value of the CT image up to a point where the acquisition is useless for diagnosis. The problem of metal artefact reduction (MAR) has been intensively studied for over 3 decades. A common approach for MAR is to discard the projection data influenced by metal. Therefore, an algorithm must be found that can cope with the gap within the acquired raw data (a sinogram). The majority of the high quantity of different approaches that have been published can be separated in two categories: sinogram completion-based methods and iterative methods.
Our research group at the Institute of Medical Engineering is particularly working on algorithms that incorporate criteria for consistent sinograms. An inpainting method that fills the gap in the raw data in a consistent way, regarding these criteria, allows for a reconstruction that uses all required projections without using the corrupted projections through metal. Another project is focused on the inclusion of prior knowledge in terms of shape and composition of implants into a reconstruction algorithm. The main idea is to use the known attenuation coefficients of the metal implant in order to reduce the streaking artefacts, which are initially caused by the projections that are influenced by metal.
Publications
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Improvement of dose calculation in radiation therapy due to metal artifact correction using the augmented likelihood image reconstruction, Journal of Applied Clinical Medical Physics, 19(3), 227–233, 2018, DOI: 10.1002/acm2.12325.
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The effects of metal artifact reduction on the retrieval of attenuation values, Journal of applied clinical medical physics, 18(1), 243–250, 2017, DOI: 10.1002/acm2.12002.
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Augmented Likelihood Image Reconstruction, IEEE Transactions on Medical Imaging, 35(1), 158–173, 2016, DOI: 10.1109/TMI.2015.2459764.
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Augmented likelihood image reconstruction with non-local prior image regularization, 145–8, 2016.
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Influence of metal segmentation on the quality of metal artifact reduction methods, 86683C, 2013, DOI: 10.1117/12.2006810.
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Quality evaluation for metal influenced CT data, 83143Y, 2012, DOI: 10.1117/12.911349.
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Modified Eulers Elastica Inpainting for Metal Artifact Reduction in CT, 310–315, 2012, DOI: 10.1007/978-3-642-28502-8_54.
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Curvelet-based Inpainting for Metal Artifact Reduction in Computed Tomography, 242–245, 2012.
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Digitale Tomosynthese - Ein neues Verfahren zur Beurteilung degenerativer Gelenkveränderungen im Vergleich zum konventionellen Röntgen, VO216_4, 2012, DOI: 10.1055/s-0032-1311150.
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L1-Regularisierung für die Computertomographie mit begrenztem Aufnahmewinkel, 147–152, 2012, DOI: 10.1007/978-3-642-28502-8_27.
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A fully 3D approach for metal artifact reduction in computed tomography, Medical Physics, 39(11), 7042–7054, 2012, DOI: 10.1118/1.4762289.
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Sparse recovery for SPECT imaging of inflammation at implants, 64, 2011.
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Reference-free ground truth metric for metal artifact evaluation in CT images, Medical Physics, 38(7), 4321–4328, 2011, DOI: 10.1118/1.3603198.
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Computed Tomography: From Photon Statistics to Modern Cone-Beam CT, Springer, Berlin, 2010, DOI: 10.1007/978-3-540-39408-2.
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Two-Step Metal Artifact Reduction Using 2D-NFFT and Spherically Symmetric Basis Functions, 3343–3345, 2010, DOI: 10.1109/NSSMIC.2010.5874424.
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Metal artifact reduction in computed tomography using nonequispaced fourier transform, 2720–2723, 2009, DOI: 10.1109/NSSMIC.2009.5401974.
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Metal Artifact Reduction From Reformatted Projections for Hip Prostheses in Multislice Helical Computed Tomography, Investigative Radiology, 44(11), 691–696, 2009, DOI: 10.1097/rli.0b013e3181b0a2f9.
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Metallartefakte in der Computertomographie. Softwarebasierte Ansätze zur Artefaktreduktion, 1213–1222, 2009.
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Spurious Structures Created by Interpolation-Based CT Metal Artifact Reduction, 72581Y, 2009, DOI: 10.1117/12.813515.
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Intersection Line Length Normalization in CT Projection Data, 77–81, 2008, DOI: 10.1007/978-3-540-78640-5_16.
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Evaluation of surrogate data quality in sinogram-based CT metal-artifact reduction, 1–10, 2008, DOI: 10.1117/12.793622.
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Comparison of Nonequispaced Fourier Transform and Polynomial based Metal Artifact Reduction Methods in Computed Tomography, 21–25, 2008, DOI: 10.1007/978-3-540-78640-5_5.
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Sinogram Inpainting for Metal Artifact Reduction in CT Images, 651–654, 2008, DOI: 10.1007/978-3-540-89208-3_155.
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CT-MAR Reconstruction Using Non-Uniform Fourier Transform, 861–865, 2008, DOI: 10.1007/978-3-540-89208-3_206.
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The λ-MLEM Algorithm: An Iterative Reconstruction Technique for Metal Artifact Reduction in CT Images, 42–47, 2007, DOI: 10.1007/978-3-540-68764-1_6.
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Two Step MLEM Algorithm for Artefact Reduction in CT Images, Computer Assisted Radiology and Surgery, 2(1:1), 38–41, 2007, DOI: 10.1007/s11548-007-0082-8.
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A Sinogram-Based Metal Artifact Suppression Strategy for Transmission Computed Tomography, 255–262, 2007.
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Statistical Image Reconstruction for Inconsistent CT Projection Data, Methods of Information in Medicine, 46(3), 261–269, 2007, DOI: 10.1160/me9041.
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Maximum-Likelihood-Ansatz zur Metallartefaktreduktion bei der Computertomographie, 36–40, 2006, DOI: 10.1007/3-540-32137-3_8.
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Modified MLEM Algorithm for Artifact Suppression in CT, 3511–3518, 2006, DOI: 10.1109/NSSMIC.2006.353757.
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Statistische Bildrekonstruktion zur Behandlung inkonsistenter Projektionsdaten der Computertomographie, 2006.
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Gewichtete MLEM-Rekonstruktion zur Artefaktreduktion in der Transmissions-Computertomographie, 345–346, 2006.
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Artefact Suppression in Computed Tomography using Iterative Reconstruction Methods, 1130–1131, 2005.
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CT Artifact Reduction with an Iterative Maximum Likelihood Approach, 44, 2005.
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Reduction of Metal Artifacts in Computed Tomography, Computer Assisted Radiology and Surgery, 1281, 1310, 2005, DOI: 10.1016/j.ics.2005.03.024.