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April 28, 2025
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Deep-learning technique boosts diagnostic ability of fast knee MRI
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More in MRI
Seven Corners launches mobile MRI program
By AuntMinnie.com staff writers
Seven Corners Healthcare, in partnership with Superior MRI Services, is launching a mobile MRI services program.
May 1, 2025
Mobile Mri 400
ARRS: MASLD diagnosis may be subject to racial factors
By Kate Madden Yee
The diagnosis of metabolic-associated steatotic liver disease (MASLD) may be influenced by ethnic, racial, and social factors.
April 28, 2025
Liver Disease Stages
AI-assisted brain MRI shows promise for improved glioma care
By Kate Madden Yee
An AI-based technique used to analyze brain MRI exams taken of children with gliomas shows promise for predicting recurrence.
April 25, 2025
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Deep-learning technique boosts diagnostic ability of fast knee MRI
By Kate Madden Yee
A new, fast deep learning-based MR imaging technique shows excellent performance for diagnosing knee injuries, researchers have reported.
April 24, 2025
2025 04 23 Ajr Vosshenrich Thumbnail
MRI tool segments over 60 abdominal organs, structures
By Amerigo Allegretto
An automated multiorgan tool can accurately segment T1-weighted abdominal MR images.
April 22, 2025
2025 04 22 Radiology Mrisegmenter Thumbnail
AI produces synthetic 3T MR images from portable scans
By Erik L. Ridley
Findings show that AI could potentially expand the utility of neuroimaging on portable MRI systems.
April 22, 2025
Figure: Improved image quality with a generative adversarial network architecture for low- to high-field-strength image translation, called LowGAN. (A–C) Top: High-field-strength (3-T) and low-field-strength (64-mT) images and LowGAN outputs for a single participant across (A) fluid-attenuated inversion recovery (FLAIR), (B) T1-weighted (T1w), and (C) T2-weighted (T2w) contrasts. Bottom: Graphs demonstrate the structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), normalized cross-correlation (NCC), and feature similarity index (FSIM) between high field strength and low field strength (64-mT) and high field strength and LowGAN outputs. a.u. = arbitrary units.****p ≤ 0.0001. Images and caption courtesy of Radiology and the RSNA.
Machine learning standardizes bone tumor grading on MRI, CT
By Kate Madden Yee
An AI algorithm and an updated risk stratification system produce accurate and standardized bone lesion assessment on CT and MRI.
April 22, 2025
2025 04 22 Radiology Lemore Figure2 Thumbnail
Accelerated MRI protocols reduce environmental impact
By Will Morton
Accelerating MRI protocols can cut greenhouse gas emissions, energy use, and costs, while also improving patient access and revenue.
April 22, 2025
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Deep learning boosts MRI's ability to identify endometriosis
By Kate Madden Yee
Using a deep-learning model with multisequence MRI enables improved diagnostic performance for detecting endometriosis.
April 16, 2025
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MRI-based nomogram predicts breast cancer treatment response
By Amerigo Allegretto
Pretreatment breast MRI can help quantify intratumoral heterogeneity and predict pathologic complete response in breast cancer patients.
April 15, 2025
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Timely patient feedback leads to improvements in MRI exam experience
By Amerigo Allegretto
Timely MRI patient feedback can help radiologists make improvements that positively translate toward the patient experience.
April 11, 2025
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Ultrafast breast MRI determines malignant from benign markers
By Amerigo Allegretto
Ultrafast breast MRI can differentiate between markers associated with malignancy.
April 9, 2025
(A) Ultrafast MR image obtained 14 seconds after aortic enhancement shows 0.4-cm focus (arrow) in the left breast at 3-o’clock position, 4.5 cm from index cancer (not shown). (B) Ultrafast MR image obtained 23 seconds after aortic enhancement shows wash-in (arrow) of background parenchymal enhancement (BPE). (C) and (D) On first standard postcontrast subtraction MR images, focus (arrow, C) and BPE (arrow, D) are indistinguishable. MRI-guided biopsy of focus yielded grade 2 invasive lobular carcinoma. Image courtesy of the ARRS.
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