Smoothed

Ming Li, Cheng Zhang, Chengtao Peng, Yihui Guan, Pin Xu, Mingshan Sun, Jian Zheng

Abstract read

In one paragraph

Article in BioMed research international, 2016. 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

–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

2 citing papers in PubMed.

Parallel processing model for low-dose computed tomography image denoising.Visual computing for industry, biomedicine, and art · 2024
Article
Image gradient LOptics express · 2019
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

7 authors.

Ming LiMedical Imaging Department, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.

Cheng ZhangMedical Imaging Department, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.ORCID 0000-0002-2791-8271

Chengtao PengMedical Imaging Department, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.

Yihui GuanPET Center, Huashan Hospital, Fudan University, Shanghai 200235, China.

Pin XuMedical Imaging Department, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.

Mingshan SunMedical Imaging Department, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.ORCID 0000-0002-0785-7387

Jian ZhengMedical Imaging Department, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.ORCID 0000-0003-4257-331X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Low-dose computed tomography (CT) reconstruction is a challenging problem in medical imaging. To complement the standard filtered back-projection (FBP) reconstruction, sparse regularization reconstruction gains more and more research attention, as it promises to reduce radiation dose, suppress artifacts, and improve noise properties. In this work, we present an iterative reconstruction approach using improved smoothed

Indexed as

AlgorithmsAnimalsArtifactsComputer SimulationHeadHumansMiceModels, StatisticalPhantoms, ImagingRadiographic Image EnhancementRadiographic Image Interpretation, Computer-AssistedReproducibility of ResultsSignal-To-Noise RatioTomography, X-Ray Computed

Identifiers

PMID27725935

DOI10.1155/2016/2180457

PMCPMC5048096

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.