ArticleEuropean radiology2026
Advances in IPMN imaging: deep learning-enhanced HASTE improves lesion assessment.
Article in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- Assessment of Robustness of MRI Radiomic Features in Four Abdominal Organs: Impact of Deep Learning Reconstruction and Segmentation.Journal of magnetic resonance imaging : JMRI · 2026Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe prevalence of asymptomatic pancreatic cysts is increasing due to advances in imaging techniques. Among these, intraductal papillary mucinous neoplasms (IPMNs) are most common, with potential for malignant transformation, often necessitating close follow-up. This study evaluates novel MRI techniques for the assessment of IPMN. MATERIALS AND
methodsFrom May to December 2023, 59 patients undergoing abdominal MRI were retrospectively enrolled. Examinations were conducted on 3-Tesla scanners using a Deep-Learning Accelerated Half-Fourier Single-Shot Turbo Spin-Echo (HASTE
resultsHASTE
conclusionHASTE KEY POINTS: Question Are there advantages of deep-learning-accelerated MRI in imaging and assessing intraductal papillary mucinous neoplasms (IPMN)? Findings Deep-Learning Accelerated Half-Fourier Single-Shot Turbo Spin-Echo (HASTE
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