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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
Descripción
Sumario: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.