ArticleIEEE transactions on neural networks and learning systems2022
NeRP: Implicit Neural Representation Learning With Prior Embedding for Sparsely Sampled Image Reconstruction.
Article in IEEE transactions on neural networks and learning systems, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 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
35 citing papers in PubMed.
- Zero-Shot Self-Supervised Learning of Single Breath-Hold Magnetic Resonance Cholangiopancreatography (MRCP) Reconstruction.Magnetic resonance in medicine · 2026Article
- Neural Representation Learning for Compact and Efficient Modeling of Monte Carlo Phase Space Data.International journal of particle therapy · 2026Article
- On the Utility of Foundation Models for Fast MRI: Vision-Language-Guided Image Reconstruction.Magnetic resonance in medicine · 2026Article
- TransSensors (Basel, Switzerland) · 2026Article
- Cross-Distribution Diffusion Priors-Driven Iterative Reconstruction for Sparse-View CT.IEEE transactions on medical imaging · 2026Article
- Bilevel Optimized Implicit Neural Representation for Scan-Specific Accelerated MRI Reconstruction.IEEE transactions on medical imaging · 2026Article
- 'See' through the surface: surface-derived three-dimensional AI-driven real-time imaging solution for intra-treatment image guidance.Machine Learning. Health · 2026Article
- Accelerating MRI With Longitudinally-Informed Latent Posterior Sampling.Magnetic resonance in medicine · 2026Article
- Cardiac MR Fingerprinting at 0.55T Using a Deep Image Prior for Joint TJournal of magnetic resonance imaging : JMRI · 2026Article
- Accelerating Multiparametric Quantitative MRI Using Self-Supervised Scan-Specific Implicit Neural Representation With Model Reinforcement.Magnetic resonance in medicine · 2026Article
- Artificial Intelligence in Prostate MRI: Addressing Current Limitations Through Emerging Technologies.Journal of magnetic resonance imaging : JMRI · 2026Review
- Accelerated Patient-specific Non-Cartesian Magnetic Resonance Imaging Reconstruction Using Implicit Neural Representations.International journal of radiation oncology, biology, physics · 2026Article
- Cross-Domain TransNet for sparse-view CT reconstruction.Frontiers in nuclear medicine · 2026Article
- Navigator motion-resolved MR fingerprinting using implicit neural representation: Feasibility for free-breathing three-dimensional whole-liver multiparametric mapping.Magnetic resonance in medicine · 2026Article
- Prior-adapted progressive time-resolved CBCT reconstruction using a dynamic reconstruction and motion estimation method.Medical physics · 2025Article
- Deep learning-based artefact reduction in low-dose dental cone beam computed tomography with high-attenuation materials.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Review
- Spatiotemporal Implicit Neural Representation for Unsupervised Dynamic MRI Reconstruction.IEEE transactions on medical imaging · 2025Article
- Real-time CBCT imaging and motion tracking via a single arbitrarily-angled x-ray projection by a joint dynamic reconstruction and motion estimation (DREME) framework.Physics in medicine and biology · 2025Article
- Computationally Efficient Implicit Training Strategy for Unrolled Networks (IMUNNE): A Preliminary Analysis Using Accelerated Real-Time Cardiac Cine MRI.IEEE transactions on bio-medical engineering · 2025Article
- Multi-Sensor Learning Enables Information Transfer Across Different Sensory Data and Augments Multi-Modality Imaging.IEEE transactions on pattern analysis and machine intelligence · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Image reconstruction is an inverse problem that solves for a computational image based on sampled sensor measurement. Sparsely sampled image reconstruction poses additional challenges due to limited measurements. In this work, we propose a methodology of implicit Neural Representation learning with Prior embedding (NeRP) to reconstruct a computational image from sparsely sampled measurements. The method differs fundamentally from previous deep learning-based image reconstruction approaches in that NeRP exploits the internal information in an image prior and the physics of the sparsely sampled measurements to produce a representation of the unknown subject. No large-scale data is required to train the NeRP except for a prior image and sparsely sampled measurements. In addition, we demonstrate that NeRP is a general methodology that generalizes to different imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI). We also show that NeRP can robustly capture the subtle yet significant image changes required for assessing tumor progression.
Identifiers
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.