ArticleEuropean radiology2025
Deep learning super-resolution reconstruction for fast and high-quality cine cardiovascular magnetic resonance.
Article in European radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- [The digital patient journey : Performing radiological examinations].Radiologie (Heidelberg, Germany) · 2026Review
- Deep learning improves image quality in motion-robust and sedation-free pediatric brain MRI.European radiology · 2026Article
- Single-visit cardiac functional assessment by cine CT added to CCTA: segment-level validation of low-dose recirculation timing protocol.European radiology · 2026Article
- Cardiac MR function analysis with DL-based super resolution reconstruction: application in the clinical setting.The international journal of cardiovascular imaging · 2026Article
- CHARMS: A CNN-Transformer Hybrid with Attention Regularization for MRI Super-Resolution.Sensors (Basel, Switzerland) · 2026Article
- Ultra-fast whole-brain T2-weighted imaging in 7 seconds using dual-type deep learning reconstruction with single-shot acquisition: clinical feasibility and comparison with conventional methods.Japanese journal of radiology · 2026Article
- Comparative evaluation of four reconstruction techniques for prostate T2-weighted MRI: Sensitivity encoding, compressed sensing, deep learning, and super-resolution.European journal of radiology open · 2025Article
- Cardiac Magnetic Resonance Imaging in Asia: 2025 Status Update.Korean journal of radiology · 2025Article
- Low-field and portable MRI technology: advancements and innovations.European radiology experimental · 2025Review
- Accelerated brain magnetic resonance imaging with deep learning reconstruction: a comparative study on image quality in pediatric neuroimaging.Pediatric radiology · 2025Article
- Semi-quantitative Analysis of Right Ventricular Myocardial First-pass Perfusion Using Cardiac Magnetic Resonance Imaging in Systemic Sclerosis and Pulmonary Arterial Hypertension.Academic radiology · 2025Article
- Artificial intelligence-assisted compressed sensing CINE enhances the workflow of cardiac magnetic resonance in challenging patients.World journal of cardiology · 2025Article
- Dual-type deep learning-based image reconstruction for advanced denoising and super-resolution processing in head and neck T2-weighted imaging.Japanese journal of radiology · 2025Article
- Cardiac magnetic resonance versus echocardiography: An analysis examining risk reclassification by left ventricular ejection fraction and cost burden analysis.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2025Article
- Clinical feasibility of two cardiac deep learning cine magnetic resonance imaging sequences: Single-breath-hold and free-breathing motion-corrected approaches.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2025Article
- Ultrafast deep learning super-resolution single-shot T2-weighted imaging for robust edema visualization in cardiovascular magnetic resonance.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic ResonanceArticle
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11 authors.
Funding
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Abstract
objectivesTo compare standard-resolution balanced steady-state free precession (bSSFP) cine images with cine images acquired at low resolution but reconstructed with a deep learning (DL) super-resolution algorithm. MATERIALS AND
methodsCine cardiovascular magnetic resonance (CMR) datasets (short-axis and 4-chamber views) were prospectively acquired in healthy volunteers and patients at normal (cine
resultsThirty participants were analyzed (37 ± 16 years; 20 healthy volunteers and 10 patients). Short-axis views whole-stack acquisition duration of cine
conclusionDeep-learning reconstruction of cine images acquired at a lower spatial resolution led to a decrease in acquisition times of 42% with shorter breath-holds without affecting volumetric results or image quality. KEY POINTS: Question Cine CMR acquisitions are time-intensive and vulnerable to artifacts. Findings Low-resolution upscaled reconstructions using DL super-resolution decreased acquisition times by 35-42% without a significant difference in volumetric results or subjective image quality. Clinical relevance DL super-resolution reconstructions of bSSFP cine images acquired at a lower spatial resolution reduce acquisition times while preserving diagnostic accuracy, improving the clinical feasibility of cine imaging by decreasing breath hold duration.
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