ArticleScientific reports2023
Metal artifacts reduction in kV-CT images with polymetallic dentures and complex metals based on MV-CBCT images in radiotherapy.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 6 citations in OpenAlex.
- Dual-encoder architecture for metal artifact reduction for kV-cone-beam CT images in head and neck cancer radiotherapy.Scientific reports · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper proposes a metal artifact reduction method of using MV-CBCT images to correct metal artifacts in kV-CT images, especially for the complex metal artifacts caused by multi-metal interaction of patients with head and neck tumors. The different tissue regions are segmented in the MV-CBCT images to obtain template images and the metal region is segmented in the kV-CT images. Forward projection is performed to get sinogram of the template images, kV-CT images and metal region images. Artifact images can be reconstructed through those sonograms. Corrected images is generated by subtracting the artifact images from the original kV-CT images. After the first correction, the template images are generated again and brought into the previous step for iteration to get better correction result. CT data set of 7 patients are used in this study, compared with linear interpolation metal artifact (LIMAR) and normalized metal artifact reduction method, mean relative error of CT value is reduced by 50.5% and 63.3%, noise is reduced by 56.2% and 58.9%. The Identifiability Score of the tooth, upper/lower jaw, tongue, lips, masseter muscle and cavity in the corrected images by the proposed method have significantly improved (P < 0.05) than original images. The artifacts correction method proposed in this paper can effectively remove the metal artifacts in the images and greatly improve the CT value accuracy, especially in the case of multi-metal and complex metal implantation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.