A metal artifact reduction algorithm in CT using multiple prior images by recursive active contour segmentation

Nam, Haewon; Baek, Jongduk

doi:10.1371/journal.pone.0179022

Cited by 10 publications

(6 citation statements)

References 30 publications

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“…Image reconstruction on CT scanners usually include a series of correction steps for beam hardening, scattered radiation and noise measurement. However, in the presence of metal implants these corrections may not be sufficient [31, 32]. The impact of metal artefacts/distortion of images varies depending on the type of radiation treatment and the size of the metallic implants, as well as the location of these implants relative to the treatment site [16].…”

Section: Discussionmentioning

confidence: 99%

Fiducial markers visibility and artefacts in prostate cancer radiotherapy multi-modality imaging

et al. 2019

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BackgroundIn this study, a novel pelvic phantom was developed and used to assess the visibility and presence of artefacts from different types of commercial fiducial markers (FMs) on multi-modality imaging relevant to prostate cancer.Methods and materialsThe phantom was designed with 3D printed hollow cubes in the centre. These cubes were filled with gel to mimic the prostate gland and two parallel PVC rods were used to mimic bones in the pelvic region. Each cube was filled with gelatine and three unique FMs were positioned with a clinically-relevant spatial distribution. The FMs investigated were; Gold Marker (GM) CIVCO, GM RiverPoint, GM Gold Anchor (GA) line and ball shape, and polymer marker (PM) from CIVCO. The phantom was scanned using several imaging modalities typically used to image prostate cancer patients; MRI, CT, CBCT, planar kV-pair, ExacTrac, 6MV, 2.5MV and integrated EPID imaging. The visibility of the markers and any observed artefacts in the phantom were compared to in-vivo scans of prostate cancer patients with FMs.ResultsAll GMs were visible in volumetric scans, however, they also had the most visible artefacts on CT and CBCT scans, with the magnitude of artefacts increasing with FM size. PM FMs had the least visible artefacts in volumetric scans but they were not visible on portal images and had poor visibility on lateral kV images. The smallest diameter GMs (GA) were the most difficult GMs to identify on lateral kV images.ConclusionThe choice between different FMs is also dependent on the adopted IGRT strategy. PM was found to be superior to investigated gold markers in the most commonly used modalities in the management of prostate cancer; CT, CBCT and MRI imaging.

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Section: Discussionmentioning

confidence: 99%

Fiducial markers visibility and artefacts in prostate cancer radiotherapy multi-modality imaging

et al. 2019

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“…Our method methodologically belongs to the class of prior-image-based reconstruction algorithms, where information from the prior images is used to reconstruct the corrupted areas of the original CT image. Various approaches to image segmentation, prior generation, and data interpolation proposed by different authors have proved general reliability and validity of the prior-image-based approaches [27,28].…”

Section: Introductionmentioning

confidence: 98%

Model Image-Based Metal Artifact Reduction for Computed Tomography

Luzhbin¹,

Wu²

2019

J Digit Imaging

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Metal implants often produce severe artifacts in the reconstructed computed tomography (CT) images, causing information and image detail loss and making the CT images diagnostically unusable. In order to eliminate the metal artifacts and enhance the diagnostic value of the reconstructed CT images, a post-processing metal artifact reduction algorithm, based on a tissue-class model segmented by thresholding and k-means clustering with spatial information, is proposed. The image inpainting technique is incorporated into the algorithm to improve the segmentation accuracy for CT images severely corrupted by metal artifacts. A study of a water phantom and of two sets of clinical CT images was performed to test the algorithm performance. The proposed method effectively eliminates typical metal artifacts, restores the average CT numbers of different tissues to the proper levels, and preserves the edge and contrast information, thus allowing the accurate reconstruction of the tissue attenuation map. The quality of the artifact-corrected CT images allows them to be subsequently used in other clinical applications, such as three-dimensional rendering, dose estimation for radiotherapy, attenuation correction for PET and SPECT, etc. The algorithm does not rely on the use of the raw sinogram and so is not limited by the proprietary format restrictions.

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“…In our previous work, we proposed a MAR method based on multiple prior images using a recursive active contour segmentation [ 21 ] scheme; however, when data truncation occurs, the residual artifact of the initial MAR process can cause severe distortions, thus making it difficult to apply this method. In this work, we propose a new method for MAR in small FOV imaging with data truncation.…”

Section: Introductionmentioning

confidence: 99%

A metal artifact reduction method for small field of view CT imaging

2021

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Several sinogram inpainting based metal artifact reduction (MAR) methods have been proposed to reduce metal artifact in CT imaging. The sinogram inpainting method treats metal trace regions as missing data and estimates the missing information. However, a general assumption with these methods is that data truncation does not occur and that all metal objects still reside within the field-of-view (FOV). These assumptions are usually violated when the FOV is smaller than the object. Thus, existing inpainting based MAR methods are not effective. In this paper, we propose a new MAR method to effectively reduce metal artifact in the presence of data truncation. The main principle of the proposed method involves using a newly synthesized sinogram instead of the originally measured sinogram. The initial reconstruction step involves obtaining a small FOV image with the truncation artifact removed. The final step is to conduct sinogram inpainting based MAR methods, i.e., linear and normalized MAR methods, on the synthesized sinogram from the previous step. The proposed method was verified for extended cardiac-torso simulations, clinical data, and experimental data, and its performance was quantitatively compared with those of previous methods (i.e., linear and normalized MAR methods directly applied to the originally measured sinogram data). The effectiveness of the proposed method was further demonstrated by reducing the residual metal artifact that were present in the reconstructed images obtained using the previous method.

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A metal artifact reduction algorithm in CT using multiple prior images by recursive active contour segmentation

Cited by 10 publications

References 30 publications

Fiducial markers visibility and artefacts in prostate cancer radiotherapy multi-modality imaging

Fiducial markers visibility and artefacts in prostate cancer radiotherapy multi-modality imaging

Model Image-Based Metal Artifact Reduction for Computed Tomography

A metal artifact reduction method for small field of view CT imaging

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