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Radiomics in Breast Imaging: Future Development
Breast cancer is the most common and most commonly diagnosed non-skin cancer in women. There are several risk factors related to habits and heredity, and screening is essential to reduce the incidence of mortality. Thanks to screening and increased awareness among women, most breast cancers are diag...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10220770/ https://www.ncbi.nlm.nih.gov/pubmed/37241032 http://dx.doi.org/10.3390/jpm13050862 |
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author | Panico, Alessandra Gatta, Gianluca Salvia, Antonio Grezia, Graziella Di Fico, Noemi Cuccurullo, Vincenzo |
author_facet | Panico, Alessandra Gatta, Gianluca Salvia, Antonio Grezia, Graziella Di Fico, Noemi Cuccurullo, Vincenzo |
author_sort | Panico, Alessandra |
collection | PubMed |
description | Breast cancer is the most common and most commonly diagnosed non-skin cancer in women. There are several risk factors related to habits and heredity, and screening is essential to reduce the incidence of mortality. Thanks to screening and increased awareness among women, most breast cancers are diagnosed at an early stage, increasing the chances of cure and survival. Regular screening is essential. Mammography is currently the gold standard for breast cancer diagnosis. In mammography, we can encounter problems with the sensitivity of the instrument; in fact, in the case of a high density of glands, the ability to detect small masses is reduced. In fact, in some cases, the lesion may not be particularly evident, it may be hidden, and it is possible to incur false negatives as partial details that may escape the radiologist’s eye. The problem is, therefore, substantial, and it makes sense to look for techniques that can increase the quality of diagnosis. In recent years, innovative techniques based on artificial intelligence have been used in this regard, which are able to see where the human eye cannot reach. In this paper, we can see the application of radiomics in mammography. |
format | Online Article Text |
id | pubmed-10220770 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102207702023-05-28 Radiomics in Breast Imaging: Future Development Panico, Alessandra Gatta, Gianluca Salvia, Antonio Grezia, Graziella Di Fico, Noemi Cuccurullo, Vincenzo J Pers Med Article Breast cancer is the most common and most commonly diagnosed non-skin cancer in women. There are several risk factors related to habits and heredity, and screening is essential to reduce the incidence of mortality. Thanks to screening and increased awareness among women, most breast cancers are diagnosed at an early stage, increasing the chances of cure and survival. Regular screening is essential. Mammography is currently the gold standard for breast cancer diagnosis. In mammography, we can encounter problems with the sensitivity of the instrument; in fact, in the case of a high density of glands, the ability to detect small masses is reduced. In fact, in some cases, the lesion may not be particularly evident, it may be hidden, and it is possible to incur false negatives as partial details that may escape the radiologist’s eye. The problem is, therefore, substantial, and it makes sense to look for techniques that can increase the quality of diagnosis. In recent years, innovative techniques based on artificial intelligence have been used in this regard, which are able to see where the human eye cannot reach. In this paper, we can see the application of radiomics in mammography. MDPI 2023-05-20 /pmc/articles/PMC10220770/ /pubmed/37241032 http://dx.doi.org/10.3390/jpm13050862 Text en © 2023 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 Panico, Alessandra Gatta, Gianluca Salvia, Antonio Grezia, Graziella Di Fico, Noemi Cuccurullo, Vincenzo Radiomics in Breast Imaging: Future Development |
title | Radiomics in Breast Imaging: Future Development |
title_full | Radiomics in Breast Imaging: Future Development |
title_fullStr | Radiomics in Breast Imaging: Future Development |
title_full_unstemmed | Radiomics in Breast Imaging: Future Development |
title_short | Radiomics in Breast Imaging: Future Development |
title_sort | radiomics in breast imaging: future development |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10220770/ https://www.ncbi.nlm.nih.gov/pubmed/37241032 http://dx.doi.org/10.3390/jpm13050862 |
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