ArticleScientific reports2023
Image quality assessment using deep learning in high b-value diffusion-weighted breast MRI.
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 12 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
12 citing papers in PubMed.
- Adapted foundation models for breast MRI triaging in contrast-enhanced and non-contrast-enhanced protocols.European radiology · 2026Article
- Influence of co-registration on lesion characterization in diffusion-weighted breast MRI.Magma (New York, N.Y.) · 2026Article
- Can AI Detect What Is Not Injected? Evaluation of Lesion Detection in Virtual Contrast-Enhanced Breast MRI Using a Large-Scale AI Model Trained on GBCA-Enhanced Data.Tomography (Ann Arbor, Mich.) · 2026Article
- Artificial intelligence improves radiologist workflow and assessment of image quality accuracy.Bioinformation · 2026Article
- Including AI in diffusion-weighted breast MRI has potential to increase reader confidence and reduce workload.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Explainable Radiomics-Based Model for Automatic Image Quality Assessment in Breast Cancer DCE MRI Data.Journal of imaging · 2025Article
- Virtual contrast-enhanced maximum intensity projections from high-b-value diffusion-weighted breast MRI: a feasibility study.European radiology experimental · 2025Article
- Impact of non-contrast-enhanced imaging input sequences on the generation of virtual contrast-enhanced breast MRI scans using neural network.European radiology · 2025Article
- AI Applications to Breast MRI: Today and Tomorrow.Journal of magnetic resonance imaging : JMRI · 2024Review
- Smart forecasting of artifacts in contrast-enhanced breast MRI before contrast agent administration.European radiology · 2024Article
- Diffusion-Weighted Imaging for Skin Pathologies of the Breast-A Feasibility Study.Diagnostics (Basel, Switzerland) · 2024Article
- Lesion-conditioning of synthetic MRI-derived subtraction-MIPs of the breast using a latent diffusion model.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The objective of this IRB approved retrospective study was to apply deep learning to identify magnetic resonance imaging (MRI) artifacts on maximum intensity projections (MIP) of the breast, which were derived from diffusion weighted imaging (DWI) protocols. The dataset consisted of 1309 clinically indicated breast MRI examinations of 1158 individuals (median age [IQR]: 50 years [16.75 years]) acquired between March 2017 and June 2020, in which a DWI sequence with a high b-value equal to 1500 s/mm
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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 Socratic graph.