Cargando…

Radiomics for Everyone: A New Tool Simplifies Creating Parametric Maps for the Visualization and Quantification of Radiomics Features

Aim was to develop a user-friendly method for creating parametric maps that would provide a comprehensible visualization and allow immediate quantification of radiomics features. For this, a self-explanatory graphical user interface was designed, and for the proof of concept, maps were created for C...

Descripción completa

Detalles Bibliográficos
Autores principales: Kim, Damon, Jensen, Laura J., Elgeti, Thomas, Steffen, Ingo G., Hamm, Bernd, Nagel, Sebastian N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8482265/
https://www.ncbi.nlm.nih.gov/pubmed/34564303
http://dx.doi.org/10.3390/tomography7030041
_version_ 1784576867352707072
author Kim, Damon
Jensen, Laura J.
Elgeti, Thomas
Steffen, Ingo G.
Hamm, Bernd
Nagel, Sebastian N.
author_facet Kim, Damon
Jensen, Laura J.
Elgeti, Thomas
Steffen, Ingo G.
Hamm, Bernd
Nagel, Sebastian N.
author_sort Kim, Damon
collection PubMed
description Aim was to develop a user-friendly method for creating parametric maps that would provide a comprehensible visualization and allow immediate quantification of radiomics features. For this, a self-explanatory graphical user interface was designed, and for the proof of concept, maps were created for CT and MR images and features were compared to those from conventional extractions. Especially first-order features were concordant between maps and conventional extractions, some even across all examples. Potential clinical applications were tested on CT and MR images for the differentiation of pulmonary lesions. In these sample applications, maps of Skewness enhanced the differentiation of non-malignant lesions and non-small lung carcinoma manifestations on CT images and maps of Variance enhanced the differentiation of pulmonary lymphoma manifestations and fungal infiltrates on MR images. This new and simple method for creating parametric maps makes radiomics features visually perceivable, allows direct feature quantification by placing a region of interest, can improve the assessment of radiological images and, furthermore, can increase the use of radiomics in clinical routine.
format Online
Article
Text
id pubmed-8482265
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-84822652021-10-01 Radiomics for Everyone: A New Tool Simplifies Creating Parametric Maps for the Visualization and Quantification of Radiomics Features Kim, Damon Jensen, Laura J. Elgeti, Thomas Steffen, Ingo G. Hamm, Bernd Nagel, Sebastian N. Tomography Article Aim was to develop a user-friendly method for creating parametric maps that would provide a comprehensible visualization and allow immediate quantification of radiomics features. For this, a self-explanatory graphical user interface was designed, and for the proof of concept, maps were created for CT and MR images and features were compared to those from conventional extractions. Especially first-order features were concordant between maps and conventional extractions, some even across all examples. Potential clinical applications were tested on CT and MR images for the differentiation of pulmonary lesions. In these sample applications, maps of Skewness enhanced the differentiation of non-malignant lesions and non-small lung carcinoma manifestations on CT images and maps of Variance enhanced the differentiation of pulmonary lymphoma manifestations and fungal infiltrates on MR images. This new and simple method for creating parametric maps makes radiomics features visually perceivable, allows direct feature quantification by placing a region of interest, can improve the assessment of radiological images and, furthermore, can increase the use of radiomics in clinical routine. MDPI 2021-09-17 /pmc/articles/PMC8482265/ /pubmed/34564303 http://dx.doi.org/10.3390/tomography7030041 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kim, Damon
Jensen, Laura J.
Elgeti, Thomas
Steffen, Ingo G.
Hamm, Bernd
Nagel, Sebastian N.
Radiomics for Everyone: A New Tool Simplifies Creating Parametric Maps for the Visualization and Quantification of Radiomics Features
title Radiomics for Everyone: A New Tool Simplifies Creating Parametric Maps for the Visualization and Quantification of Radiomics Features
title_full Radiomics for Everyone: A New Tool Simplifies Creating Parametric Maps for the Visualization and Quantification of Radiomics Features
title_fullStr Radiomics for Everyone: A New Tool Simplifies Creating Parametric Maps for the Visualization and Quantification of Radiomics Features
title_full_unstemmed Radiomics for Everyone: A New Tool Simplifies Creating Parametric Maps for the Visualization and Quantification of Radiomics Features
title_short Radiomics for Everyone: A New Tool Simplifies Creating Parametric Maps for the Visualization and Quantification of Radiomics Features
title_sort radiomics for everyone: a new tool simplifies creating parametric maps for the visualization and quantification of radiomics features
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8482265/
https://www.ncbi.nlm.nih.gov/pubmed/34564303
http://dx.doi.org/10.3390/tomography7030041
work_keys_str_mv AT kimdamon radiomicsforeveryoneanewtoolsimplifiescreatingparametricmapsforthevisualizationandquantificationofradiomicsfeatures
AT jensenlauraj radiomicsforeveryoneanewtoolsimplifiescreatingparametricmapsforthevisualizationandquantificationofradiomicsfeatures
AT elgetithomas radiomicsforeveryoneanewtoolsimplifiescreatingparametricmapsforthevisualizationandquantificationofradiomicsfeatures
AT steffeningog radiomicsforeveryoneanewtoolsimplifiescreatingparametricmapsforthevisualizationandquantificationofradiomicsfeatures
AT hammbernd radiomicsforeveryoneanewtoolsimplifiescreatingparametricmapsforthevisualizationandquantificationofradiomicsfeatures
AT nagelsebastiann radiomicsforeveryoneanewtoolsimplifiescreatingparametricmapsforthevisualizationandquantificationofradiomicsfeatures