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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Grapho Publications, LLC
2020
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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. |
format | Online Article Text |
id | pubmed-7289253 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Grapho Publications, LLC |
record_format | MEDLINE/PubMed |
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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