Evidence map›Paper›PMID 41669415›Full record

ArticleQuantitative imaging in medicine and surgery2026

Acquisition of K

Jingfei Li, Mu Du, Yubao Liu, Daohui Zeng, Long Yang, Xuanle Li, Greta S P Mok, Ke Zhang, Jing Qin, Xin Liu and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2026. 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

15 authors.

Jingfei Li *College of Information Science and Engineering, Northeastern University, Shenyang, China.
Mu Du *Medical Imaging Center, Shenzhen Hospital, Southern Medical University, Shenzhen, China.
Yubao LiuMedical Imaging Center, Shenzhen Hospital, Southern Medical University, Shenzhen, China.
Daohui ZengPaul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Long YangPaul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Xuanle LiPaul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Greta S P MokBiomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau SAR, China.
Ke ZhangDepartment of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany.
Jing QinCentre for Smart Health, School of Nursing, The Hong Kong Polytechnic University, Hong Kong, China.
Xin LiuPaul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Dong LiangPaul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Zhanli HuPaul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Hairong ZhengPaul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Bo YuanDepartment of Neurology, The Fourth People's Hospital of Shenzhen, Shenzhen, China.
Na ZhangPaul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Traditional methods for calculating perfusion parameter maps such as K Methods: A pix2pix-based conditional generative adversarial networks (cGAN) architecture was proposed to generate breast K Results: The best performance was obtained when synthesizing K Conclusions: The synthesis of breast K

Indexed as

Breast cancerdeep learning (DL)dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)magnetic resonance imaging (MRI)perfusion parameter maps

Identifiers

PMID41669415
PMCPMC12883527

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.