Open Access
4 December 2018 Variation in algorithm implementation across radiomics software
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Abstract
Given the increased need for consistent quantitative image analysis, variations in radiomics feature calculations due to differences in radiomics software were investigated. Two in-house radiomics packages and two freely available radiomics packages, MaZda and IBEX, were utilized. Forty 256  ×  256-pixel regions of interest (ROIs) from 40 digital mammograms were studied along with 39 manually delineated ROIs from the head and neck (HN) computed tomography (CT) scans of 39 patients. Each package was used to calculate first-order histogram and second-order gray-level co-occurrence matrix (GLCM) features. Friedman tests determined differences in feature values across packages, whereas intraclass-correlation coefficients (ICC) quantified agreement. All first-order features computed from both mammography and HN cases (except skewness in mammography) showed significant differences across all packages due to systematic biases introduced by each package; however, based on ICC values, all but one first-order feature calculated on mammography ROIs and all but two first-order features calculated on HN CT ROIs showed excellent agreement, indicating the observed differences were small relative to the feature values but the bias was systematic. All second-order features computed from the two databases both differed significantly and showed poor agreement among packages, due largely to discrepancies in package-specific default GLCM parameters. Additional differences in radiomics features were traced to variations in image preprocessing, algorithm implementation, and naming conventions. Large variations in features among software packages indicate that increased efforts to standardize radiomics processes must be conducted.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Joseph J. Foy, Kayla R. Robinson, Hui Li, Maryellen L. Giger, Hania Al-Hallaq, and Samuel G. Armato "Variation in algorithm implementation across radiomics software," Journal of Medical Imaging 5(4), 044505 (4 December 2018). https://doi.org/10.1117/1.JMI.5.4.044505
Received: 17 May 2018; Accepted: 30 October 2018; Published: 4 December 2018
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CITATIONS
Cited by 66 scholarly publications.
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KEYWORDS
Mammography

Computed tomography

Photovoltaics

Medical imaging

Feature extraction

Image segmentation

Nomenclature

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