ArticleTomography (Ann Arbor, Mich.)2023
Retrospective Motion Artifact Reduction by Spatial Scaling of Liver Diffusion-Weighted Images.
Article in Tomography (Ann Arbor, Mich.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed, 4 citations in OpenAlex.
- 5.0 T versus 1.5 T and 3.0 T upper abdominal MRI: a prospective two‑cohort study of image quality and diagnostic confidence.European radiology · 2026Article
- Adaptive Complex Signal Average Diffusion-Weighted MR Imaging of the Liver: Utility in Breath-Hold Imaging: A Retrospective Single-Center Study.Tomography (Ann Arbor, Mich.) · 2026Article
- Usefulness of Adaptive Complex Signal Average Diffusion-weighted MR Imaging of the Abdomen.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026Article
- Transforming Medical Imaging: The Role of Artificial Intelligence Integration in PACS for Enhanced Diagnostic Accuracy and Workflow EfficiencyCurrent medical imaging · 2025Review
- Robust multishot diffusion-weighted imaging of the abdomen with region-based shot rejection.Magnetic resonance in medicine · 2024Article
- Clinical Applications of Artificial Intelligence in Medical Imaging and Image Processing-A Review.Cancers · 2024Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiac motion causes unpredictable signal loss in respiratory-triggered diffusion-weighted magnetic resonance imaging (DWI) of the liver, especially inside the left lobe. The left liver lobe may thus be frequently neglected in the clinical evaluation of liver DWI. In this work, a data-driven algorithm that relies on the statistics of the signal in the left liver lobe to mitigate the motion-induced signal loss is presented. The proposed data-driven algorithm utilizes the exclusion of severely corrupted images with subsequent spatially dependent image scaling based on a signal-loss model to correctly combine the multi-average diffusion-weighted images. The signal in the left liver lobe is restored and the liver signal is more homogeneous after applying the proposed algorithm. Furthermore, overestimation of the apparent diffusion coefficient (ADC) in the left liver lobe is reduced. The proposed algorithm can therefore contribute to reduce the motion-induced bias in DWI of the liver and help to increase the diagnostic value of DWI in the left liver lobe.
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Registered trials
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