Evidence map›Paper›PMID 41270750›Full record

ArticleCell reports methods2025

Real-time 4D MRI reconstruction using DVR-NeMF, a framework for dynamic volumetric reconstruction.

Ruoxi Wang, Sijie Zhong, Jincheng Li, Weifeng Zhang, Shunwen Zheng, Ziyong Hao, Shuyu Liu, Xin Fang, Rushi Jiao, Yizhe Yuan and 7 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell reports methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Ruoxi WangSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Sijie ZhongSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Jincheng LiSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Weifeng ZhangShanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.
Shunwen ZhengShanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.
Ziyong HaoShanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.
Shuyu LiuSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Xin FangSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Rushi JiaoSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Yizhe YuanSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Bingsen XueSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Ning DingPublic Security Behavior Science Lab, People's Public Security University of China, Beijing 100091, China.
Yanfeng WangShanghai Artificial Intelligence Laboratory, Shanghai 200232, China; School of Electronic Information and Electronical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Ya ZhangShanghai Artificial Intelligence Laboratory, Shanghai 200232, China; School of Electronic Information and Electronical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Hongjiang WeiSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Zhiyong ZhangSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Cheng JinSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China; The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 100088, China; Chinese National Clinical Research Center for Kidney Diseases, Beijing 100853, China. Electronic address: chengjin520@sjtu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, four dynamic magnetic resonance imaging (MRI) sequences were first developed to collect data. On this basis, we presented DVR-NeMF, a neural magnetic field framework that enables real-time, high-dimensional (4D) MRI reconstruction from synchronized dynamic 2D image slices and physiological signals. By embedding spatiotemporal priors into an implicit representation of the imaging space, DVR-NeMF reconstructs temporally consistent 3D volumes over time with high anatomical fidelity. Comprehensive evaluations across a cardiovascular phantom, cardiac dynamic bio-simulators, and living human hearts, including external out-of-distribution validation on the Automated Cardiac Diagnosis Challenge (ACDC) dataset, demonstrated that DVR-NeMF outperforms both autoencoder- and generative adversarial network (GAN)-based baselines in terms of reconstruction accuracy and computational efficiency. Comparative analysis with paired cardiac ultrasound data in terms of key left ventricular function parameters further confirmed its reliability. This work offers a promising paradigm for extending MRI to dynamic, high-dimensional imaging, with potential for real-time functional assessment in clinical settings.

Indexed as

HeartImage Processing, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingAlgorithmsHumansPhantoms, ImagingReproducibility of ResultsCP: computational biologyCP: imagingdynamic volumetric reconstructionmagnetic resonance imagingneural magnetic fieldspatiotemporal priors

Identifiers

PMID41270750
PMCPMC12859481

What OpenQuestion holds

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Registered trials

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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.