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Stanford DRO Toolkit: Digital Reference Objects for Standardization of Radiomic Features

Several institutions have developed image feature extraction software to compute quantitative descriptors of medical images for radiomics analyses. With radiomics increasingly proposed for use in research and clinical contexts, new techniques are necessary for standardizing and replicating radiomics...

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Detalles Bibliográficos
Autores principales: Jaggi, Akshay, Mattonen, Sarah A., McNitt-Gray, Michael, Napel, Sandy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Grapho Publications, LLC 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289253/
https://www.ncbi.nlm.nih.gov/pubmed/32548287
http://dx.doi.org/10.18383/j.tom.2019.00030
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author Jaggi, Akshay
Mattonen, Sarah A.
McNitt-Gray, Michael
Napel, Sandy
author_facet Jaggi, Akshay
Mattonen, Sarah A.
McNitt-Gray, Michael
Napel, Sandy
author_sort Jaggi, Akshay
collection PubMed
description Several institutions have developed image feature extraction software to compute quantitative descriptors of medical images for radiomics analyses. With radiomics increasingly proposed for use in research and clinical contexts, new techniques are necessary for standardizing and replicating radiomics findings across software implementations. We have developed a software toolkit for the creation of 3D digital reference objects with customizable size, shape, intensity, texture, and margin sharpness values. Using user-supplied input parameters, these objects are defined mathematically as continuous functions, discretized, and then saved as DICOM objects. Here, we present the definition of these objects, parameterized derivations of a subset of their radiomics values, computer code for object generation, example use cases, and a user-downloadable sample collection used for the examples cited in this paper.
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spelling pubmed-72892532020-06-15 Stanford DRO Toolkit: Digital Reference Objects for Standardization of Radiomic Features Jaggi, Akshay Mattonen, Sarah A. McNitt-Gray, Michael Napel, Sandy Tomography Research Articles Several institutions have developed image feature extraction software to compute quantitative descriptors of medical images for radiomics analyses. With radiomics increasingly proposed for use in research and clinical contexts, new techniques are necessary for standardizing and replicating radiomics findings across software implementations. We have developed a software toolkit for the creation of 3D digital reference objects with customizable size, shape, intensity, texture, and margin sharpness values. Using user-supplied input parameters, these objects are defined mathematically as continuous functions, discretized, and then saved as DICOM objects. Here, we present the definition of these objects, parameterized derivations of a subset of their radiomics values, computer code for object generation, example use cases, and a user-downloadable sample collection used for the examples cited in this paper. Grapho Publications, LLC 2020-06 /pmc/articles/PMC7289253/ /pubmed/32548287 http://dx.doi.org/10.18383/j.tom.2019.00030 Text en © 2020 The Authors. Published by Grapho Publications, LLC http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Articles
Jaggi, Akshay
Mattonen, Sarah A.
McNitt-Gray, Michael
Napel, Sandy
Stanford DRO Toolkit: Digital Reference Objects for Standardization of Radiomic Features
title Stanford DRO Toolkit: Digital Reference Objects for Standardization of Radiomic Features
title_full Stanford DRO Toolkit: Digital Reference Objects for Standardization of Radiomic Features
title_fullStr Stanford DRO Toolkit: Digital Reference Objects for Standardization of Radiomic Features
title_full_unstemmed Stanford DRO Toolkit: Digital Reference Objects for Standardization of Radiomic Features
title_short Stanford DRO Toolkit: Digital Reference Objects for Standardization of Radiomic Features
title_sort stanford dro toolkit: digital reference objects for standardization of radiomic features
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289253/
https://www.ncbi.nlm.nih.gov/pubmed/32548287
http://dx.doi.org/10.18383/j.tom.2019.00030
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