Evidence map›Paper›PMID 27502957›Full record

ArticleTechnology in cancer research & treatment2017

Sensitivity of Image Features to Noise in Conventional and Respiratory-Gated PET/CT Images of Lung Cancer: Uncorrelated Noise Effects.

Jasmine A Oliver, Mikalai Budzevich, Dylan Hunt, Eduardo G Moros, Kujtim Latifi, Thomas J Dilling, Vladimir Feygelman, Geoffrey Zhang

Open access · bronzeAbstract read
In one paragraph

Article in Technology in cancer research & treatment, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

13 citing papers in PubMed, 23 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Jasmine A Oliver1 Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA.
Mikalai Budzevich3 Small Animal Imaging Laboratory, Moffitt Cancer Center, Tampa, FL, USA.
Dylan Hunt1 Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA.
Eduardo G Moros1 Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA.
Kujtim Latifi1 Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA.
Thomas J Dilling1 Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA.
Vladimir Feygelman1 Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA.
Geoffrey Zhang1 Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA.
Moffitt Cancer Center · USUniversity of South Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The effect of noise on image features has yet to be studied in depth. Our objective was to explore how significantly image features are affected by the addition of uncorrelated noise to an image. The signal-to-noise ratio and noise power spectrum were calculated for a positron emission tomography/computed tomography scanner using a Ge-68 phantom. The conventional and respiratory-gated positron emission tomography/computed tomography images of 31 patients with lung cancer were retrospectively examined. Multiple sets of noise images were created for each original image by adding Gaussian noise of varying standard deviation equal to 2.5%, 4.0%, and 6.0% of the maximum intensity for positron emission tomography images and 10, 20, 50, 80, and 120 Hounsfield units for computed tomography images. Image features were extracted from all images, and percentage differences between the original image and the noise image feature values were calculated. These features were then categorized according to the noise sensitivity. The contour-dependent shape descriptors averaged below 4% difference in positron emission tomography and below 13% difference in computed tomography between noise and original images. Gray level size zone matrix features were the most sensitive to uncorrelated noise exhibiting average differences >200% for conventional and respiratory-gated images in computed tomography and 90% in positron emission tomography. Image feature differences increased as the noise level increased for shape, intensity, and gray-level co-occurrence matrix features in positron emission tomography and for gray-level co-occurrence matrix and gray-level size zone matrix features in conventional computed tomography. Investigators should be aware of the noise effects on image features.

Indexed as

Image Processing, Computer-AssistedPositron Emission Tomography Computed TomographyAgedAged, 80 and overAlgorithmsFemaleHumansLung NeoplasmsMaleMiddle AgedPhantoms, ImagingSensitivity and SpecificitySignal-To-Noise Ratioimage feature analysisimage noiselung cancerPET/CTradiomics

Identifiers

PMID27502957
PMCPMC5665151
OpenAlexW2520586201

What OpenQuestion holds

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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.