Evidence map›Paper›PMID 34238745›Full record

ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2021

[Extraction of respiratory signals from chest tomosynthesis].

Q Li, J Liu, Y Mo, J Yu, K Zhang, H Zhang

Open access · greenAbstract read
In one paragraph

Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2021. 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, top 87% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

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

6 authors at 1 institution in 1 country.

Q LiSchool of Biomedical Engineering, Southern Medical University, Guangzhou 510000 China.
J LiuSchool of Biomedical Engineering, Southern Medical University, Guangzhou 510000 China.
Y MoSchool of Biomedical Engineering, Southern Medical University, Guangzhou 510000 China.
J YuSchool of Biomedical Engineering, Southern Medical University, Guangzhou 510000 China.
K ZhangSchool of Biomedical Engineering, Southern Medical University, Guangzhou 510000 China.
H ZhangSchool of Biomedical Engineering, Southern Medical University, Guangzhou 510000 China.
Southern Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo analyze the respiratory motion of the scanned object during acquisition of digital chest tomosynthesis (CTS) using a linear model.

objectiveRespiratory signals were generated by extracting the motion of the diaphragm from the projection radiographs. The diaphragm trajectory obtained by dynamic programming (DP) was modeled and fitted, and according to the fitting of the data, the base motion curve and respiratory signal curve of the diaphragm were separated. Multipurpose chest phantom data, simulated digital Xcat phantom data and the datasets of 3 clinical patients were used to validate the performance of the proposed method.

objectiveThe motion trajectory of the diaphragm extracted from multipurpose chest phantom simulation data was linear. The respiratory signals could be effectively extracted from the 3 datasets of clinical patients in different respiratory states. The correlation coefficient between the respiratory signal extracted in Xcat simulation experiment and the original design was 0.9797.

objectiveThe linear model can effectively obtain the respiratory motion information of patients in real time, thus enabling the physicians to make clinical decisions on a rescan.

Indexed as

RespirationComputer SimulationHumansMotionPhantoms, Imagingchest tomosynthesismotion analysisrespiratory signals

Identifiers

PMID34238745
PMCPMC8267983
OpenAlexW3179351475

What OpenQuestion holds

Textmetadata
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.