Evidence map›Paper›PMID 35360269›Full record

ArticleContrast media & molecular imaging2022

Artificial Intelligence Algorithm-Based Magnetic Resonance Imaging to Evaluate the Effect of Radiation Synovectomy for Hemophilic Arthropathy.

Heng Zhang, Shukai Duan, Wei Xiao, Xinyue Yang, Shenglin Li

Open access · hybridAbstract read
In one paragraph

Article in Contrast media & molecular imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 42% of its field
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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Reshaping Anesthesia with Artificial Intelligence: From Concept to Reality.Anesthesia and critical care (Houston, Tex.) · 2025
    Article
  2. Article
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

5 authors at 3 institutions in 2 countries.

Heng ZhangCollege of Mathematics and Statistics, Southwest University, Chongqing 400715, China.ORCID 0000-0001-5588-063X
Shukai DuanCollege of Artificial Intelligence, Southwest University, Chongqing 400715, China.ORCID 0000-0001-5878-4424
Wei XiaoDepartment of Military Logistics, Army Logistic University of PLA, Chongqing 401331, China.ORCID 0000-0002-9423-3184
Xinyue YangCollege of Artificial Intelligence, Southwest University, Chongqing 400715, China.ORCID 0000-0003-4300-2789
Shenglin LiCollege of Artificial Intelligence, Southwest University, Chongqing 400715, China.ORCID 0000-0003-3740-6250
Intel (United States) · USPLA Army Service Academy · CNSouthwest University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to discuss magnetic resonance imaging (MRI) based on artificial intelligence (AI) algorithm to evaluate the effect of radiation synovectomy for hemophilic arthropathy (HA). MRI based on the Canny algorithm was applied and compared with conventional MRI to evaluate its application effects according to the PSNR and SSIM. Sixty patients diagnosed with HA were selected as the research subjects. According to the detection method, the patients were divided into group A (pathological detection after radiation synovectomy), group B (conventional MRI detection), and group C (MRI detection based on the Canny algorithm). The application value of MRI based on the Canny algorithm was judged by comparing the differences between the two detection methods and pathological results. The results displayed that the reconstruction effect of the Canny algorithm was remarkably better than that of the traditional algorithm regarding the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM), which showed a clearer synovial contour. The results of the IPSG score of joint effusion and hemorrhage showed that there was a difference in the detection rate of joints between conventional MRI and pathological results on the score of 1 and 2 (

Indexed as

Joint DiseasesSynovectomyAlgorithmsArtificial IntelligenceHumansMagnetic Resonance Imaging

Identifiers

PMID35360269
PMCPMC8957465
OpenAlexW4220776553

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.