Two methods for reducing moving metal artifacts in cone-beam CT

• Verfasst von: Hahn, Andreas [VerfasserIn]
• Verfasst von: Knaup, Michael [VerfasserIn]
• Verfasst von: Brehm, Marcus [VerfasserIn]
• Verfasst von: Sauppe, Sebastian [VerfasserIn]
• Verfasst von: Kachelrieß, Marc [VerfasserIn]
• Titel: Two methods for reducing moving metal artifacts in cone-beam CT
• Verf.angabe: Andreas Hahn, Michael Knaup, Marcus Brehm, Sebastian Sauppe, Marc Kachelrieß
• E-Jahr: 2018
• Jahr: 25 June 2018
• Umfang: 10 S.
• Fussnoten: Gesehen am 20.08.2019
• Titel Quelle: Enthalten in: Medical physics
• Ort Quelle: Hoboken, NJ : Wiley, 1974
• Jahr Quelle: 2018
• Band/Heft Quelle: 45(2018), 8, Seite 3671-3680
• ISSN Quelle: 2473-4209
• ISSN Quelle: 1522-8541
• DOI: doi:10.1002/mp.13060
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Cone-beam CT
• Sach-SW: image-guided radiation therapy
• Sach-SW: moving metal artifact reduction
• Sach-SW: sinogram inpainting
• K10plus-PPN: 1671642821

Abstract

Purpose In image-guided radiation therapy, fiducial markers or clips are often used to determine the position of the tumor. These markers lead to streak artifacts in cone-beam CT (CBCT) scans. Standard inpainting-based metal artifact reduction (MAR) methods fail to remove these artifacts in cases of large motion. We propose two methods to effectively reduce artifacts caused by moving metal inserts. Methods The first method (MMAR) utilizes a coarse metal segmentation in the image domain and a refined segmentation in the rawdata domain. After an initial reconstruction, metal is segmented and forward projected giving a coarse metal mask in the rawdata domain. Inside the coarse mask, metal is segmented by utilizing a 2D Sobel filter. Metal is removed by linear interpolation in the refined metal mask. The second method (MoCoMAR) utilizes a motion compensation (MoCo) algorithm [Med Phys. 2013;40:101913] that provides us with a motion-free volume (3D) or with a time series of motion-free volumes (4D). We then apply the normalized metal artifact reduction (NMAR) [Med Phys. 2010;37:5482-5493] to these MoCo volumes. Both methods were applied to three CBCT data sets of patients with metal inserts in the thorax or abdomen region and a 4D thorax simulation. The results were compared to volumes corrected by a standard MAR1 [Radiology. 1987;164:576-577]. Results MMAR and MoCoMAR were able to remove all artifacts caused by moving metal inserts for the patients and the simulation. Both new methods outperformed the standard MAR1, which was only able to remove artifacts caused by metal inserts with little or no motion. Conclusions In this work, two new methods to remove artifacts caused by moving metal inserts are introduced. Both methods showed good results for a simulation and three patients. While the first method (MMAR) works without any prior knowledge, the second method (MoCoMAR) requires a respiratory signal for the MoCo step and is computationally more demanding and gives no benefit over MMAR, unless MoCo images are desired.