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Related Concept Videos

Imaging Studies IV: Magnetic Resonance Imaging01:27

Imaging Studies IV: Magnetic Resonance Imaging

Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...
Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

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Related Experiment Video

Updated: May 28, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Quantification of edge-enhancing effects using accelerated deep learning reconstructed orbital MRI sequences.

Christer Ruff1, Deborah Staber1, Georg Gohla1

  • 1Department of Diagnostic and Interventional Neuroradiology, Eberhard Karls University Tuebingen, Tuebingen D-72076, Germany.

European Journal of Radiology Open
|May 27, 2026
PubMed
Summary
This summary is machine-generated.

Accelerated deep learning reconstruction in orbital MRI improves image sharpness and reduces scan time. However, careful interpretation is needed due to potentially reduced internal anatomical detail.

Keywords:
BlurrinessDeep learning reconstructionEdge sharpnessMagnetic resonance imagingOrbitTurbo spin-echo

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Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
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Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

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Area of Science:

  • Radiology
  • Medical Imaging
  • Artificial Intelligence in Medicine

Background:

  • Conventional MRI sequences can be time-consuming.
  • Deep learning (DL) offers potential for accelerated image reconstruction.

Purpose of the Study:

  • To compare image quality, sharpness, and internal structure delineation between accelerated deep learning-reconstructed (TSEDLR) and conventional (TSECR) turbo spin-echo sequences in 3T orbital MRI.

Main Methods:

  • Retrospective analysis of 25 patients undergoing 3T orbital MRI with both conventional and accelerated (up to 75%) DL-reconstructed TSE sequences.
  • Qualitative assessment by two blinded neuroradiologists using a 5-point Likert scale.
  • Quantitative analysis of image metrics, sharpness (PSI), blur, and edge parameters.

Main Results:

  • TSEDLR demonstrated superior qualitative and quantitative edge and overall sharpness, particularly in T1-weighted contrast-enhanced fat-saturated sequences.
  • Quantitative analysis showed improved edge steepness and reduced edge width with TSEDLR, alongside higher PSI and SNR/PSNR.
  • Structural similarity was high, but high-frequency similarity was lower with TSEDLR. Blur metrics favored TSECR, and internal delineation was rater-dependent.

Conclusions:

  • Accelerated DL-based reconstructions maintain or enhance lesion conspicuity and image quality in orbital MRI, significantly reducing scan time.
  • While edge sharpness is improved, reduced internal anatomical delineation necessitates cautious interpretation of TSEDLR images.