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Radiomics in Breast Imaging from Techniques to Clinical Applications: A Review

Recent advances in computer technology have generated a new area of research known as radiomics. Radiomics is defined as the high throughput extraction and analysis of quantitative features from imaging data. Radiomic features provide information on the gray-scale patterns, inter-pixel relationships...

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Detalles Bibliográficos
Autores principales: Lee, Seung-Hak, Park, Hyunjin, Ko, Eun Sook
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Radiology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289696/
https://www.ncbi.nlm.nih.gov/pubmed/32524780
http://dx.doi.org/10.3348/kjr.2019.0855
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author Lee, Seung-Hak
Park, Hyunjin
Ko, Eun Sook
author_facet Lee, Seung-Hak
Park, Hyunjin
Ko, Eun Sook
author_sort Lee, Seung-Hak
collection PubMed
description Recent advances in computer technology have generated a new area of research known as radiomics. Radiomics is defined as the high throughput extraction and analysis of quantitative features from imaging data. Radiomic features provide information on the gray-scale patterns, inter-pixel relationships, as well as shape and spectral properties of radiological images. Moreover, these features can be used to develop computational models that may serve as a tool for personalized diagnosis and treatment guidance. Although radiomics is becoming popular and widely used in oncology, many problems such as overfitting and reproducibility issues remain unresolved. In this review, we will outline the steps of radiomics used for oncology, specifically addressing applications for breast cancer patients and focusing on technical issues.
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spelling pubmed-72896962020-07-01 Radiomics in Breast Imaging from Techniques to Clinical Applications: A Review Lee, Seung-Hak Park, Hyunjin Ko, Eun Sook Korean J Radiol Breast Imaging Recent advances in computer technology have generated a new area of research known as radiomics. Radiomics is defined as the high throughput extraction and analysis of quantitative features from imaging data. Radiomic features provide information on the gray-scale patterns, inter-pixel relationships, as well as shape and spectral properties of radiological images. Moreover, these features can be used to develop computational models that may serve as a tool for personalized diagnosis and treatment guidance. Although radiomics is becoming popular and widely used in oncology, many problems such as overfitting and reproducibility issues remain unresolved. In this review, we will outline the steps of radiomics used for oncology, specifically addressing applications for breast cancer patients and focusing on technical issues. The Korean Society of Radiology 2020-07 2020-05-29 /pmc/articles/PMC7289696/ /pubmed/32524780 http://dx.doi.org/10.3348/kjr.2019.0855 Text en Copyright © 2020 The Korean Society of Radiology http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Breast Imaging
Lee, Seung-Hak
Park, Hyunjin
Ko, Eun Sook
Radiomics in Breast Imaging from Techniques to Clinical Applications: A Review
title Radiomics in Breast Imaging from Techniques to Clinical Applications: A Review
title_full Radiomics in Breast Imaging from Techniques to Clinical Applications: A Review
title_fullStr Radiomics in Breast Imaging from Techniques to Clinical Applications: A Review
title_full_unstemmed Radiomics in Breast Imaging from Techniques to Clinical Applications: A Review
title_short Radiomics in Breast Imaging from Techniques to Clinical Applications: A Review
title_sort radiomics in breast imaging from techniques to clinical applications: a review
topic Breast Imaging
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289696/
https://www.ncbi.nlm.nih.gov/pubmed/32524780
http://dx.doi.org/10.3348/kjr.2019.0855
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