Evidence map›Paper›PMID 34394893›Full record

ArticleJournal of healthcare engineering2021

Study on Model Iterative Reconstruction Algorithm vs. Filter Back Projection Algorithm for Diagnosis of Acute Cerebral Infarction Using CT Images.

Songlin Tang, Yan Liu, Zhifu Wang, Yajie Liu, Huafei Liu

Open access · hybridAbstract read
In one paragraph

Article in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 55% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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 1 institution in 1 country.

Songlin TangDepartment of Neurology, The First Affiliated Hospital of Shaoyang College, Shaoyang 422039, Hunan, China.ORCID 0000-0003-3333-2098
Yan LiuDepartment of Imaging, Shaoyang Central Hospital, Shaoyang 422100, Hunan, China.ORCID 0000-0002-0586-5404
Zhifu WangDepartment of Neurology, The First Affiliated Hospital of Shaoyang College, Shaoyang 422039, Hunan, China.ORCID 0000-0002-4178-3086
Yajie LiuDepartment of Neurology, The First Affiliated Hospital of Shaoyang College, Shaoyang 422039, Hunan, China.ORCID 0000-0002-6581-5062
Huafei LiuDepartment of Neurology, The First Affiliated Hospital of Shaoyang College, Shaoyang 422039, Hunan, China.ORCID 0000-0002-6135-6567
The Central Hospital of Shaoyang · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim was to explore the application value of computed tomography (CT) perfusion (CTP) imaging based on the iterative model reconstruction (IMR) in the diagnosis of acute cerebral infarction (ACI). 80 patients with ACI, admitted to hospital, were selected as the research objects and divided randomly into a routine treatment group (group A) and a low-dose group (group B) (each group with 40 patients). Patients in group A were scanned at 80 kV-150 mAs, and the traditional filtered back projection (FBP) algorithm was employed to reconstruct the images; besides, 80 kV-30 mAs was adopted to scan the patients in group B, and the images were reconstructed by IMR1, IMR2, IMR3, iDose4 (a kind of hybrid iterative reconstruction technology), and FBP, respectively. The application values of different algorithms were evaluated by CTP based on the collected CTP images of patients and detecting indicators. The results showed that the gray and white matter CT value, SD value, SNR, CNR, and subjective image scores of patients in group B were basically consistent with those of group A (

Indexed as

Radiographic Image Interpretation, Computer-AssistedTomography, X-Ray ComputedAlgorithmsCerebral InfarctionHumansRadiation Dosage

Identifiers

PMID34394893
PMCPMC8360711
OpenAlexW3187498329

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.