Evidence map›Paper›PMID 23990913›Full record

ArticlePloS one2013

jClustering, an open framework for the development of 4D clustering algorithms.

José María Mateos-Pérez, Carmen García-Villalba, Javier Pascau, Manuel Desco, Juan J Vaquero

Abstract read
In one paragraph

Article in PloS one, 2013. 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
–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

1 citing paper in PubMed.

  1. Review
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.

José María Mateos-PérezInstituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain ; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain.
Carmen García-Villalba
Javier Pascau
Manuel Desco
Juan J Vaquero

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present jClustering, an open framework for the design of clustering algorithms in dynamic medical imaging. We developed this tool because of the difficulty involved in manually segmenting dynamic PET images and the lack of availability of source code for published segmentation algorithms. Providing an easily extensible open tool encourages publication of source code to facilitate the process of comparing algorithms and provide interested third parties with the opportunity to review code. The internal structure of the framework allows an external developer to implement new algorithms easily and quickly, focusing only on the particulars of the method being implemented and not on image data handling and preprocessing. This tool has been coded in Java and is presented as an ImageJ plugin in order to take advantage of all the functionalities offered by this imaging analysis platform. Both binary packages and source code have been published, the latter under a free software license (GNU General Public License) to allow modification if necessary.

Indexed as

Computer GraphicsProgramming LanguagesAlgorithmsBrainCluster AnalysisContrast MediaHumansImage Processing, Computer-AssistedInternetMagnetic Resonance ImagingPositron-Emission TomographyPrincipal Component AnalysisSoftwareUser-Computer InterfaceContrast Media

Identifiers

PMID23990913
PMCPMC3750055

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.