ArticleEuropean journal of radiology open2026
Quantification of edge-enhancing effects using accelerated deep learning reconstructed orbital MRI sequences.
Article in European journal of radiology open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Rationale and Objectives: To qualitatively and quantitatively compare image quality, edge sharpness, and internal-structure delineation of accelerated deep learning-reconstructed turbo spin-echo (TSE Materials and Methods: Twenty-five patients undergoing 3 T orbital MRI were retrospectively selected. All underwent conventional and accelerated (up to 75%) deep learning-reconstructed axial and coronal T2-weighted and contrast-enhanced fat-saturated T1-weighted TSE (T1CEfs) sequences. Two blinded neuroradiologists rated image quality, edge sharpness, internal tissue delineation, overall sharpness, lesion detection confidence, and lesion conspicuity on a 5-point Likert scale. Quantitative analyses included similarity and image-quality metrics, the Perceptual Sharpness Index (PSI), blur metrics, and edge parameters after Roberts, Sobel, or Canny edge extraction. Results: Qualitatively, edge and overall sharpness were superior with TSE Conclusion: Accelerated DL-based reconstructions for orbital MRI maintain or improve lesion conspicuity, overall image quality, and edge sharpness, while substantially reducing scan time. However, reduced internal anatomical delineation warrants cautious interpretation of the images.
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