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Review and Analysis of Tumour Detection and Image Quality Analysis in Experimental Breast Microwave Sensing

This review evaluates the methods used for image quality analysis and tumour detection in experimental breast microwave sensing (BMS), a developing technology being investigated for breast cancer detection. This article examines the methods used for image quality analysis and the estimated diagnosti...

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Detalles Bibliográficos
Autores principales: Reimer, Tyson, Pistorius, Stephen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10255334/
https://www.ncbi.nlm.nih.gov/pubmed/37299852
http://dx.doi.org/10.3390/s23115123
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author Reimer, Tyson
Pistorius, Stephen
author_facet Reimer, Tyson
Pistorius, Stephen
author_sort Reimer, Tyson
collection PubMed
description This review evaluates the methods used for image quality analysis and tumour detection in experimental breast microwave sensing (BMS), a developing technology being investigated for breast cancer detection. This article examines the methods used for image quality analysis and the estimated diagnostic performance of BMS for image-based and machine-learning tumour detection approaches. The majority of image analysis performed in BMS has been qualitative and existing quantitative image quality metrics aim to describe image contrast—other aspects of image quality have not been addressed. Image-based diagnostic sensitivities between 63 and 100% have been achieved in eleven trials, but only four articles have estimated the specificity of BMS. The estimates range from 20 to 65%, and do not demonstrate the clinical utility of the modality. Despite over two decades of research in BMS, significant challenges remain that limit the development of this modality as a clinical tool. The BMS community should utilize consistent image quality metric definitions and include image resolution, noise, and artifacts in their analyses. Future work should include more robust metrics, estimates of the diagnostic specificity of the modality, and machine-learning applications should be used with more diverse datasets and with robust methodologies to further enhance BMS as a viable clinical technique.
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spelling pubmed-102553342023-06-10 Review and Analysis of Tumour Detection and Image Quality Analysis in Experimental Breast Microwave Sensing Reimer, Tyson Pistorius, Stephen Sensors (Basel) Review This review evaluates the methods used for image quality analysis and tumour detection in experimental breast microwave sensing (BMS), a developing technology being investigated for breast cancer detection. This article examines the methods used for image quality analysis and the estimated diagnostic performance of BMS for image-based and machine-learning tumour detection approaches. The majority of image analysis performed in BMS has been qualitative and existing quantitative image quality metrics aim to describe image contrast—other aspects of image quality have not been addressed. Image-based diagnostic sensitivities between 63 and 100% have been achieved in eleven trials, but only four articles have estimated the specificity of BMS. The estimates range from 20 to 65%, and do not demonstrate the clinical utility of the modality. Despite over two decades of research in BMS, significant challenges remain that limit the development of this modality as a clinical tool. The BMS community should utilize consistent image quality metric definitions and include image resolution, noise, and artifacts in their analyses. Future work should include more robust metrics, estimates of the diagnostic specificity of the modality, and machine-learning applications should be used with more diverse datasets and with robust methodologies to further enhance BMS as a viable clinical technique. MDPI 2023-05-27 /pmc/articles/PMC10255334/ /pubmed/37299852 http://dx.doi.org/10.3390/s23115123 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 Review
Reimer, Tyson
Pistorius, Stephen
Review and Analysis of Tumour Detection and Image Quality Analysis in Experimental Breast Microwave Sensing
title Review and Analysis of Tumour Detection and Image Quality Analysis in Experimental Breast Microwave Sensing
title_full Review and Analysis of Tumour Detection and Image Quality Analysis in Experimental Breast Microwave Sensing
title_fullStr Review and Analysis of Tumour Detection and Image Quality Analysis in Experimental Breast Microwave Sensing
title_full_unstemmed Review and Analysis of Tumour Detection and Image Quality Analysis in Experimental Breast Microwave Sensing
title_short Review and Analysis of Tumour Detection and Image Quality Analysis in Experimental Breast Microwave Sensing
title_sort review and analysis of tumour detection and image quality analysis in experimental breast microwave sensing
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10255334/
https://www.ncbi.nlm.nih.gov/pubmed/37299852
http://dx.doi.org/10.3390/s23115123
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