Analysis and classification of lung tissue in ultrasound images for pneumonia detection

Pneumonia is an infection of the lungs caused by virus, bacteria or fungi. It affects mainly children under five and can be life-threatening. Diagnosis of pneumonia is usually performed using imaging techniques such as chest radiography, ultrasound, and CT. Several studies have shown that ultrasound...

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Autores:
Valdes-Burgos, L.
Contreras Ojeda, Sara
Domínguez Jiménez, Juan Antonio
López-Bueno J.
Contreras Ortiz, Sonia Helena
Tipo de recurso:
Fecha de publicación:
2020
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/9517
Acceso en línea:
https://hdl.handle.net/20.500.12585/9517
https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11330/1133003/Analysis-and-classification-of-lung-tissue-in-ultrasound-images-for/10.1117/12.2542615.short
Palabra clave:
Pneumonia
Structure of parenchyma of lung
Principal Component Analysis
Plain chest X-ray
Imaging Techniques
Accidental Falls
Cross Infection
Radiographic imaging procedure
Rights
closedAccess
License
http://purl.org/coar/access_right/c_14cb
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dc.title.spa.fl_str_mv Analysis and classification of lung tissue in ultrasound images for pneumonia detection
title Analysis and classification of lung tissue in ultrasound images for pneumonia detection
spellingShingle Analysis and classification of lung tissue in ultrasound images for pneumonia detection
Pneumonia
Structure of parenchyma of lung
Principal Component Analysis
Plain chest X-ray
Imaging Techniques
Accidental Falls
Cross Infection
Radiographic imaging procedure
title_short Analysis and classification of lung tissue in ultrasound images for pneumonia detection
title_full Analysis and classification of lung tissue in ultrasound images for pneumonia detection
title_fullStr Analysis and classification of lung tissue in ultrasound images for pneumonia detection
title_full_unstemmed Analysis and classification of lung tissue in ultrasound images for pneumonia detection
title_sort Analysis and classification of lung tissue in ultrasound images for pneumonia detection
dc.creator.fl_str_mv Valdes-Burgos, L.
Contreras Ojeda, Sara
Domínguez Jiménez, Juan Antonio
López-Bueno J.
Contreras Ortiz, Sonia Helena
dc.contributor.author.none.fl_str_mv Valdes-Burgos, L.
Contreras Ojeda, Sara
Domínguez Jiménez, Juan Antonio
López-Bueno J.
Contreras Ortiz, Sonia Helena
dc.subject.keywords.spa.fl_str_mv Pneumonia
Structure of parenchyma of lung
Principal Component Analysis
Plain chest X-ray
Imaging Techniques
Accidental Falls
Cross Infection
Radiographic imaging procedure
topic Pneumonia
Structure of parenchyma of lung
Principal Component Analysis
Plain chest X-ray
Imaging Techniques
Accidental Falls
Cross Infection
Radiographic imaging procedure
description Pneumonia is an infection of the lungs caused by virus, bacteria or fungi. It affects mainly children under five and can be life-threatening. Diagnosis of pneumonia is usually performed using imaging techniques such as chest radiography, ultrasound, and CT. Several studies have shown that ultrasound is an effective, safe and cost-efficient technique for pneumonia detection. However, due to the low signal-to-noise ratio of the images, this technique is highly dependent on the experience of the practitioner. This paper proposes an approach for pneumonia detection from image texture features. We used empirical mode decomposition for feature extraction, principal component analysis for dimensionality reduction and supervised learning methods for classification. Results show that features of the first mode present large differences between healthy and pneumonia patients according to the Cohen’s d index. Pneumonia detection was possible with a rotation forest model with a mean accuracy of 83.33%.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-10-30T16:30:36Z
dc.date.available.none.fl_str_mv 2020-10-30T16:30:36Z
dc.date.issued.none.fl_str_mv 2020-01-03
dc.date.submitted.none.fl_str_mv 2020-10-28
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dc.identifier.citation.spa.fl_str_mv L. Valdes-Burgos, S. L. Contreras-Ojeda, J. A. Domínguez-Jiménez, J. Lopez-Bueno, and S. H. Contreras-Ortiz "Analysis and classification of lung tissue in ultrasound images for pneumonia detection", Proc. SPIE 11330, 15th International Symposium on Medical Information Processing and Analysis, 1133003 (3 January 2020); https://doi.org/10.1117/12.2542615
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/9517
dc.identifier.url.none.fl_str_mv https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11330/1133003/Analysis-and-classification-of-lung-tissue-in-ultrasound-images-for/10.1117/12.2542615.short
dc.identifier.doi.none.fl_str_mv 10.1117/12.2542615
dc.identifier.instname.spa.fl_str_mv Universidad Tecnológica de Bolívar
dc.identifier.reponame.spa.fl_str_mv Repositorio Universidad Tecnológica de Bolívar
identifier_str_mv L. Valdes-Burgos, S. L. Contreras-Ojeda, J. A. Domínguez-Jiménez, J. Lopez-Bueno, and S. H. Contreras-Ortiz "Analysis and classification of lung tissue in ultrasound images for pneumonia detection", Proc. SPIE 11330, 15th International Symposium on Medical Information Processing and Analysis, 1133003 (3 January 2020); https://doi.org/10.1117/12.2542615
10.1117/12.2542615
Universidad Tecnológica de Bolívar
Repositorio Universidad Tecnológica de Bolívar
url https://hdl.handle.net/20.500.12585/9517
https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11330/1133003/Analysis-and-classification-of-lung-tissue-in-ultrasound-images-for/10.1117/12.2542615.short
dc.language.iso.spa.fl_str_mv eng
language eng
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dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.place.spa.fl_str_mv Cartagena de Indias
dc.source.spa.fl_str_mv Proceedings Volume 11330, 15th International Symposium on Medical Information Processing and Analysis; 1133003 (2020)
institution Universidad Tecnológica de Bolívar
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spelling Valdes-Burgos, L.898f2ee7-bc48-48db-8e19-aaaf71b2428eContreras Ojeda, Sara2f78dd6b-33ca-46d8-a5a0-bc083e4cd7e2Domínguez Jiménez, Juan Antoniod2ff9be0-9c22-42f6-a0eb-ce74b44b6ab2López-Bueno J.5b81ac56-074b-4769-a4fb-97ff02492ec6Contreras Ortiz, Sonia Helena690f7c84-d6e0-464a-b059-47146b2f92f52020-10-30T16:30:36Z2020-10-30T16:30:36Z2020-01-032020-10-28L. Valdes-Burgos, S. L. Contreras-Ojeda, J. A. Domínguez-Jiménez, J. Lopez-Bueno, and S. H. Contreras-Ortiz "Analysis and classification of lung tissue in ultrasound images for pneumonia detection", Proc. SPIE 11330, 15th International Symposium on Medical Information Processing and Analysis, 1133003 (3 January 2020); https://doi.org/10.1117/12.2542615https://hdl.handle.net/20.500.12585/9517https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11330/1133003/Analysis-and-classification-of-lung-tissue-in-ultrasound-images-for/10.1117/12.2542615.short10.1117/12.2542615Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarPneumonia is an infection of the lungs caused by virus, bacteria or fungi. It affects mainly children under five and can be life-threatening. Diagnosis of pneumonia is usually performed using imaging techniques such as chest radiography, ultrasound, and CT. Several studies have shown that ultrasound is an effective, safe and cost-efficient technique for pneumonia detection. However, due to the low signal-to-noise ratio of the images, this technique is highly dependent on the experience of the practitioner. This paper proposes an approach for pneumonia detection from image texture features. We used empirical mode decomposition for feature extraction, principal component analysis for dimensionality reduction and supervised learning methods for classification. Results show that features of the first mode present large differences between healthy and pneumonia patients according to the Cohen’s d index. 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