ReviewJournal of digital imaging2023
Deep Learning for Image Enhancement and Correction in Magnetic Resonance Imaging-State-of-the-Art and Challenges.
Review in Journal of digital imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
72 citing papers in PubMed, 172 citations in OpenAlex.
- New pulse sequence for improving cardiac black-blood and PSIR MRI quality in cases of arrhythmia.Magnetic resonance letters · 2027Article
- Deep learning reconstruction enables accelerated T2-weighted MRI for rectal cancer staging: a prospective study of diagnostic consistency across NEX value reduction.Abdominal radiology (New York) · 2026Article
- Shortening MRI scanning time for acute ischemic stroke: analysis of the effect of 3.0T MRI compressed sensing deep learning reconstruction.Emergency radiology · 2026Article
- Comments on "Shortening MRI scanning time for acute ischemic stroke: analysis of the effect of 3.0T MRI compressed sensing deep learning reconstruction".Emergency radiology · 2026Article
- Article
- Self-Supervised Stacked Masked Denoising Autoencoder (SSensors (Basel, Switzerland) · 2026Article
- Artificial Intelligence-Assisted Colonoscopy for Colorectal Lesion Detection: Current Evidence, Challenges, and Future Directions.Journal of clinical medicine · 2026Review
- Deep learning-based prostate cancer diagnosis on MRI with hip prostheses: artifact and sequence effects.Abdominal radiology (New York) · 2026Article
- Enhancing automated fracture detection in paediatric wrist X-rays with paired and unpaired cast suppression methods.International journal of computer assisted radiology and surgery · 2026Article
- Group-Aware Registration for Lesion-Level Quantitative Motion Correction in Respiratory-Gated PET/CT Biomedical Imaging.Sensors (Basel, Switzerland) · 2026Article
- Magnetic Resonance Imaging Preprocessing for Robust Spinal Cord Segmentation in Cervical Myelopathy.Journal of imaging · 2026Article
- Let distortion-guided restoration: a physics-informed learning framework to correct prostate diffusion MRI artifacts.Radiology advances · 2026Article
- The role of diffusion-weighted MRI in biological image-guided radiation therapy: a roadmap.Physics in medicine and biology · 2026Review
- Quantification of edge-enhancing effects using accelerated deep learning reconstructed orbital MRI sequences.European journal of radiology open · 2026Article
- A Novel MR Cine Sialography Technique for Evaluating Salivary Gland Function: Correlation with Unstimulated and Stimulated Saliva Volumes.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026Article
- A Hierarchical Multi-View Deep Learning Framework for Autism Classification Using Structural and Functional MRI.Journal of imaging · 2026Article
- Optimizing high-resolution knee MRI at 3 tesla: conventional acceleration versus deep learning reconstruction.BMC medical imaging · 2026Article
- Short-TR Acquisition Time-of-flight MR Angiography with Deep Learning Reconstruction: Technical Feasibility and Initial Clinical Evaluation in Moyamoya Disease.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026Article
- A Deep-Learning Approach for Vocal Fold Pose Estimation in Videoendoscopy.Journal of imaging informatics in medicine · 2026Article
- Deep learning reconstruction improves detection of focal liver lesions in hepatobiliary phase compared to conventional EOB-MRI.Frontiers in medicine · 2026Article
12 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Magnetic resonance imaging (MRI) provides excellent soft-tissue contrast for clinical diagnoses and research which underpin many recent breakthroughs in medicine and biology. The post-processing of reconstructed MR images is often automated for incorporation into MRI scanners by the manufacturers and increasingly plays a critical role in the final image quality for clinical reporting and interpretation. For image enhancement and correction, the post-processing steps include noise reduction, image artefact correction, and image resolution improvements. With the recent success of deep learning in many research fields, there is great potential to apply deep learning for MR image enhancement, and recent publications have demonstrated promising results. Motivated by the rapidly growing literature in this area, in this review paper, we provide a comprehensive overview of deep learning-based methods for post-processing MR images to enhance image quality and correct image artefacts. We aim to provide researchers in MRI or other research fields, including computer vision and image processing, a literature survey of deep learning approaches for MR image enhancement. We discuss the current limitations of the application of artificial intelligence in MRI and highlight possible directions for future developments. In the era of deep learning, we highlight the importance of a critical appraisal of the explanatory information provided and the generalizability of deep learning algorithms in medical imaging.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.