Evidence map›Paper›PMID 27180182›Full record

ArticleMedical & biological engineering & computing2017

Voxel-based comparative analysis of lung lesions in CT for therapeutic purposes.

Stelmo Magalhães Barros Netto, Aristófanes Corrêa Silva, Rodolfo Acatauassú Nunes, Marcelo Gattass

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Medical & biological engineering & computing, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

4 authors.

Stelmo Magalhães Barros NettoFederal University of Maranhão - UFMA, São Luís, Brazil. nobnet2000@yahoo.com.br.
Aristófanes Corrêa SilvaFederal University of Maranhão - UFMA, São Luís, Brazil.
Rodolfo Acatauassú NunesState University of Rio de Janeiro - UERJ, Rio de Janeiro, Brazil.
Marcelo GattassPontifical Catholic University of Rio de Janeiro - PUC-Rio, Rio de Janeiro, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer remains as one of the most incident types of cancer throughout the world. Temporal evaluation has become a very useful tool when one wishes to analyze some malignancy-indicating behavior. The objective of the present work is to detect changes in the local densities of lung lesions over time (follow-up analysis). From the detected changes, local information as well as extent region of changes can complement the studies regarding the malignant or benign nature of the lesion. Based on this idea, we attempt to use techniques that allow the observation of changes in the lesion over time, based on remote sensing techniques which highlight changes occurring in the environment. The techniques used were the image differencing, image rationing, median filtering, image regression and the fuzzy XOR operator. Based on the global measurement of change percentage in the density, we found density variations which were considered significant in a range from 2.22 to 36.57 % of the volume of the lesion. The results achieved are promising since, besides the visual aspects of the changes in density of the lung lesion over time, we managed to quantify these changes and compare them by volumetric analysis, a more commonly used technique for analysis of changes in lung lesions.

Indexed as

Databases, FactualFuzzy LogicHumansImage Processing, Computer-AssistedLungLung NeoplasmsTomography, X-Ray ComputedDetection of changes in tissuesLung lesionMedical imageTemporal analysis and evaluation

Identifiers

What OpenQuestion holds

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Registered trials

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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.