Proposal for computer-aided diagnosis based on ultrasound images of the kidney: is it possible to compare shades of gray among such images?

Detalhes bibliográficos
Autor(a) principal: Siqueira,Gustavo Lopes Gomes de
Data de Publicação: 2021
Outros Autores: Sousa,Robson Pequeno de, Olinda,Ricardo Alves de, Engelhorn,Carlos Alberto, Silva,André Luiz Siqueira da, Almeida,Juliana Gonçalves
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Radiologia Brasileira (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842021000100007
Resumo: Abstract Objective: To compare ultrasound images of the kidney obtained, randomly or in a controlled manner (standardizing the physical aspects of the ultrasound system), by various professionals and with different devices. Materials and Methods: We evaluated a total of 919 images of kidneys, obtained by five professionals using two types of ultrasound systems, in 24 patients. The images were categorized into four types, by how they were acquired and processed. We compared the gray-scale median and different gray-scale ranges representative of virtual histological tissues. Results: There were statistically significant differences among the five professionals, regardless of the type of ultrasound system employed, in terms of the gray-scale medians for the images obtained (p < 2.2e-16). Analyzing the four categories of images-a totally random image (without any standardization); a standardized image (with fixed values for gain, time gain control, and dynamic range); a normalized version of the random image; and a normalized version of the standardized image-we determined that the random image, even after normalization, differed quite significantly among the professionals (p = 0.006098). The analysis of the normalized version of the standardized image did not differ significantly among the professionals (p = 0.7319). Conclusion: Our findings indicate that a gray-scale analysis of ultrasound images of the kidney performs better when the image acquisition process is standardized and the images undergo a process of normalization.
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spelling Proposal for computer-aided diagnosis based on ultrasound images of the kidney: is it possible to compare shades of gray among such images?Diagnosis, computer-assistedKidney/diagnostic imagingUltrasonography/methodsUltrasonography, interventional/methodsImage processing, computer-assisted/methodsAbstract Objective: To compare ultrasound images of the kidney obtained, randomly or in a controlled manner (standardizing the physical aspects of the ultrasound system), by various professionals and with different devices. Materials and Methods: We evaluated a total of 919 images of kidneys, obtained by five professionals using two types of ultrasound systems, in 24 patients. The images were categorized into four types, by how they were acquired and processed. We compared the gray-scale median and different gray-scale ranges representative of virtual histological tissues. Results: There were statistically significant differences among the five professionals, regardless of the type of ultrasound system employed, in terms of the gray-scale medians for the images obtained (p < 2.2e-16). Analyzing the four categories of images-a totally random image (without any standardization); a standardized image (with fixed values for gain, time gain control, and dynamic range); a normalized version of the random image; and a normalized version of the standardized image-we determined that the random image, even after normalization, differed quite significantly among the professionals (p = 0.006098). The analysis of the normalized version of the standardized image did not differ significantly among the professionals (p = 0.7319). Conclusion: Our findings indicate that a gray-scale analysis of ultrasound images of the kidney performs better when the image acquisition process is standardized and the images undergo a process of normalization.Publicação do Colégio Brasileiro de Radiologia e Diagnóstico por Imagem2021-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842021000100007Radiologia Brasileira v.54 n.1 2021reponame:Radiologia Brasileira (Online)instname:Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR)instacron:CBR10.1590/0100-3984.2019.0138info:eu-repo/semantics/openAccessSiqueira,Gustavo Lopes Gomes deSousa,Robson Pequeno deOlinda,Ricardo Alves deEngelhorn,Carlos AlbertoSilva,André Luiz Siqueira daAlmeida,Juliana Gonçalveseng2021-01-29T00:00:00Zoai:scielo:S0100-39842021000100007Revistahttps://www.scielo.br/j/rb/https://old.scielo.br/oai/scielo-oai.phpradiologiabrasileira@cbr.org.br1678-70990100-3984opendoar:2021-01-29T00:00Radiologia Brasileira (Online) - Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR)false
dc.title.none.fl_str_mv Proposal for computer-aided diagnosis based on ultrasound images of the kidney: is it possible to compare shades of gray among such images?
title Proposal for computer-aided diagnosis based on ultrasound images of the kidney: is it possible to compare shades of gray among such images?
spellingShingle Proposal for computer-aided diagnosis based on ultrasound images of the kidney: is it possible to compare shades of gray among such images?
Siqueira,Gustavo Lopes Gomes de
Diagnosis, computer-assisted
Kidney/diagnostic imaging
Ultrasonography/methods
Ultrasonography, interventional/methods
Image processing, computer-assisted/methods
title_short Proposal for computer-aided diagnosis based on ultrasound images of the kidney: is it possible to compare shades of gray among such images?
title_full Proposal for computer-aided diagnosis based on ultrasound images of the kidney: is it possible to compare shades of gray among such images?
title_fullStr Proposal for computer-aided diagnosis based on ultrasound images of the kidney: is it possible to compare shades of gray among such images?
title_full_unstemmed Proposal for computer-aided diagnosis based on ultrasound images of the kidney: is it possible to compare shades of gray among such images?
title_sort Proposal for computer-aided diagnosis based on ultrasound images of the kidney: is it possible to compare shades of gray among such images?
author Siqueira,Gustavo Lopes Gomes de
author_facet Siqueira,Gustavo Lopes Gomes de
Sousa,Robson Pequeno de
Olinda,Ricardo Alves de
Engelhorn,Carlos Alberto
Silva,André Luiz Siqueira da
Almeida,Juliana Gonçalves
author_role author
author2 Sousa,Robson Pequeno de
Olinda,Ricardo Alves de
Engelhorn,Carlos Alberto
Silva,André Luiz Siqueira da
Almeida,Juliana Gonçalves
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Siqueira,Gustavo Lopes Gomes de
Sousa,Robson Pequeno de
Olinda,Ricardo Alves de
Engelhorn,Carlos Alberto
Silva,André Luiz Siqueira da
Almeida,Juliana Gonçalves
dc.subject.por.fl_str_mv Diagnosis, computer-assisted
Kidney/diagnostic imaging
Ultrasonography/methods
Ultrasonography, interventional/methods
Image processing, computer-assisted/methods
topic Diagnosis, computer-assisted
Kidney/diagnostic imaging
Ultrasonography/methods
Ultrasonography, interventional/methods
Image processing, computer-assisted/methods
description Abstract Objective: To compare ultrasound images of the kidney obtained, randomly or in a controlled manner (standardizing the physical aspects of the ultrasound system), by various professionals and with different devices. Materials and Methods: We evaluated a total of 919 images of kidneys, obtained by five professionals using two types of ultrasound systems, in 24 patients. The images were categorized into four types, by how they were acquired and processed. We compared the gray-scale median and different gray-scale ranges representative of virtual histological tissues. Results: There were statistically significant differences among the five professionals, regardless of the type of ultrasound system employed, in terms of the gray-scale medians for the images obtained (p < 2.2e-16). Analyzing the four categories of images-a totally random image (without any standardization); a standardized image (with fixed values for gain, time gain control, and dynamic range); a normalized version of the random image; and a normalized version of the standardized image-we determined that the random image, even after normalization, differed quite significantly among the professionals (p = 0.006098). The analysis of the normalized version of the standardized image did not differ significantly among the professionals (p = 0.7319). Conclusion: Our findings indicate that a gray-scale analysis of ultrasound images of the kidney performs better when the image acquisition process is standardized and the images undergo a process of normalization.
publishDate 2021
dc.date.none.fl_str_mv 2021-02-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842021000100007
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842021000100007
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0100-3984.2019.0138
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Publicação do Colégio Brasileiro de Radiologia e Diagnóstico por Imagem
publisher.none.fl_str_mv Publicação do Colégio Brasileiro de Radiologia e Diagnóstico por Imagem
dc.source.none.fl_str_mv Radiologia Brasileira v.54 n.1 2021
reponame:Radiologia Brasileira (Online)
instname:Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR)
instacron:CBR
instname_str Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR)
instacron_str CBR
institution CBR
reponame_str Radiologia Brasileira (Online)
collection Radiologia Brasileira (Online)
repository.name.fl_str_mv Radiologia Brasileira (Online) - Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR)
repository.mail.fl_str_mv radiologiabrasileira@cbr.org.br
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