Evidence map›Paper›PMID 37938518›Full record

ArticlePhysical and engineering sciences in medicine2024

Quality improvement of images with metal artifact reduction using a noise recovery technique in computed tomography.

Yusuke Morioka, Katsuhiro Ichikawa, Hiroki Kawashima

Abstract read
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In one paragraph

Article in Physical and engineering sciences in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 51% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. A comparative study of artifact reduction techniques in metal-implanted CT scans.International journal of physiology, pathophysiology and pharmacology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Yusuke MoriokaDepartment of Medical Technology, Toyama Prefectural Central Hospital, 2-2-78 Nishinagae, Toyama, 930-8550, Japan.
Katsuhiro IchikawaFaculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa, Ishikawa, 920-0942, Japan. ichikawa@mhs.mp.kanazawa-u.ac.jp.
Hiroki KawashimaFaculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa, Ishikawa, 920-0942, Japan.
Kanazawa University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In metal artifact reduction (MAR) in computed tomography (CT) based on projection data inpainting, X-ray photon noise has not been considered in the inpainting process. This study aims to assess the effectiveness of a MAR technique incorporating noise recovery in such projection data regions, compared with existing MAR techniques based on projection data normalization (NMAR), including one with frequency splitting (FSNMAR). Phantoms simulating hip prostheses and dental fillings were scanned using a 64-row multi slice CT scanner. The projection data was processed by NMAR and NMAR with noise recovery (NRNMAR); the processed data was sent back to the CT system for reconstruction. For the phantoms and clinical cases with hip prostheses and dental fillings, images were reconstructed without MAR, and with NMAR, NRNMAR, and FSNMAR (incorporated in the CT system). To validate the efficacy of noise recovery, noise power spectra (NPSs) were measured from the images of the hip prosthesis phantom with and without metals. The artifact index (AI) was compared between NRNMAR and FSNMAR. The resultant NPSs of NRNMAR were very similar to those of phantom images with no metals, endorsing the efficacy of noise recovery. The NMAR images had unnatural noise textures and FSNMAR caused additional streaks. NRNMAR exhibited some significant improvements in these respects: It reduced the AI by as much as 66.2-88.6% compared to FSNMAR, except for the case of a unilateral prosthesis. In conclusion, NRNMAR, which simply adds white noise to the projection data, would be effective in improving the quality of CT images with metal artifacts reduction.

Indexed as

ArtifactsHip ProsthesisAlgorithmsMetalsQuality ImprovementTomography, X-Ray ComputedMetalsArtifact indexComputed tomographyMetal artifact reductionProjection data inpaintingStreak

Identifiers

PMID37938518
OpenAlexW4388499695

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.