Literature DB >> 27502957

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

Jasmine A Oliver1,2, Mikalai Budzevich3, Dylan Hunt1,2, Eduardo G Moros1,2, Kujtim Latifi1,2, Thomas J Dilling1, Vladimir Feygelman1,2, Geoffrey Zhang1,2.   

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.

Entities:  

Keywords:  PET/CT; image feature analysis; image noise; lung cancer; radiomics

Mesh:

Year:  2016        PMID: 27502957      PMCID: PMC5665151          DOI: 10.1177/1533034616661852

Source DB:  PubMed          Journal:  Technol Cancer Res Treat        ISSN: 1533-0338


  29 in total

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9.  Variability of Image Features Computed from Conventional and Respiratory-Gated PET/CT Images of Lung Cancer.

Authors:  Jasmine A Oliver; Mikalai Budzevich; Geoffrey G Zhang; Thomas J Dilling; Kujtim Latifi; Eduardo G Moros
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