Automatic detection of pneumonia analyzing ultrasound digital images

Ronald Barrientos; Avid Roman-Gonzalez; Franklin Barrientos; Leonardo Solis; Malena Correa; Monica Pajuelo; Cynthia Anticona; Roberto Lavarello; Benjamin Castaneda; Richard Oberhelman; William Checkley; Robert H. Gilman; Mirko Zimic

doi:10.1109/CONCAPAN.2016.7942375

Automatic detection of pneumonia analyzing ultrasound digital images

Ronald Barrientos, Avid Roman-Gonzalez, Franklin Barrientos, Leonardo Solis, Malena Correa, Monica Pajuelo, Cynthia Anticona, Roberto Lavarello, Benjamin Castaneda, Richard Oberhelman, William Checkley, Robert H. Gilman, Mirko Zimic

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Scopus citations

Abstract

Pneumonia is one of the major causes of child mortality. Unfortunately, in developing countries there is a lack of infrastructure and medical experts in rural areas to provide the required diagnostics opportunely. Lung ultrasound echography has proved to be an important tool to detect lung consolidates as evidence of pneumonia. This paper presents a method for automatic diagnostics of pneumonia using ultrasound imaging of the lungs. The approach presented here is based on the analysis of patterns present in rectangular segments from the ultrasound digital images. Specific features from the characteristic vectors were obtained and classified with standard neural networks. A training and testing set of positive and negative vectors were compiled. Vectors obtained from a single patient were included only in the testing or in the training set, but never in both. Our approach was able to correctly classify vectors with evidence of pneumonia, with 91.5% sensitivity and 100% specificity.

Original language	English (US)
Title of host publication	2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781467395786
DOIs	https://doi.org/10.1109/CONCAPAN.2016.7942375
State	Published - Jun 7 2017
Event	36th IEEE Central American and Panama Convention, CONCAPAN 2016 - San Jose, Costa Rica Duration: Nov 9 2016 → Nov 11 2016

Publication series

Name	2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016

Other

Other	36th IEEE Central American and Panama Convention, CONCAPAN 2016
Country/Territory	Costa Rica
City	San Jose
Period	11/9/16 → 11/11/16

Keywords

Pneumonia
echography
image processing
remote diagnostics
ultrasound

ASJC Scopus subject areas

Modeling and Simulation
Health Informatics
Computer Networks and Communications
Computer Science Applications
Information Systems and Management
Energy Engineering and Power Technology

Access to Document

10.1109/CONCAPAN.2016.7942375

Cite this

Barrientos, R., Roman-Gonzalez, A., Barrientos, F., Solis, L., Correa, M., Pajuelo, M., Anticona, C., Lavarello, R., Castaneda, B., Oberhelman, R., Checkley, W., Gilman, R. H., & Zimic, M. (2017). Automatic detection of pneumonia analyzing ultrasound digital images. In 2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016 [7942375] (2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CONCAPAN.2016.7942375

Automatic detection of pneumonia analyzing ultrasound digital images. / Barrientos, Ronald; Roman-Gonzalez, Avid; Barrientos, Franklin et al.

2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016. Institute of Electrical and Electronics Engineers Inc., 2017. 7942375 (2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Barrientos, R, Roman-Gonzalez, A, Barrientos, F, Solis, L, Correa, M, Pajuelo, M, Anticona, C, Lavarello, R, Castaneda, B, Oberhelman, R, Checkley, W , Gilman, RH & Zimic, M 2017, Automatic detection of pneumonia analyzing ultrasound digital images. in 2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016., 7942375, 2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016, Institute of Electrical and Electronics Engineers Inc., 36th IEEE Central American and Panama Convention, CONCAPAN 2016, San Jose, Costa Rica, 11/9/16. https://doi.org/10.1109/CONCAPAN.2016.7942375

Barrientos R, Roman-Gonzalez A, Barrientos F, Solis L, Correa M, Pajuelo M et al. Automatic detection of pneumonia analyzing ultrasound digital images. In 2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016. Institute of Electrical and Electronics Engineers Inc. 2017. 7942375. (2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016). doi: 10.1109/CONCAPAN.2016.7942375

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abstract = "Pneumonia is one of the major causes of child mortality. Unfortunately, in developing countries there is a lack of infrastructure and medical experts in rural areas to provide the required diagnostics opportunely. Lung ultrasound echography has proved to be an important tool to detect lung consolidates as evidence of pneumonia. This paper presents a method for automatic diagnostics of pneumonia using ultrasound imaging of the lungs. The approach presented here is based on the analysis of patterns present in rectangular segments from the ultrasound digital images. Specific features from the characteristic vectors were obtained and classified with standard neural networks. A training and testing set of positive and negative vectors were compiled. Vectors obtained from a single patient were included only in the testing or in the training set, but never in both. Our approach was able to correctly classify vectors with evidence of pneumonia, with 91.5% sensitivity and 100% specificity.",

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AU - Oberhelman, Richard

AU - Checkley, William

AU - Gilman, Robert H.

AU - Zimic, Mirko

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PY - 2017/6/7

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N2 - Pneumonia is one of the major causes of child mortality. Unfortunately, in developing countries there is a lack of infrastructure and medical experts in rural areas to provide the required diagnostics opportunely. Lung ultrasound echography has proved to be an important tool to detect lung consolidates as evidence of pneumonia. This paper presents a method for automatic diagnostics of pneumonia using ultrasound imaging of the lungs. The approach presented here is based on the analysis of patterns present in rectangular segments from the ultrasound digital images. Specific features from the characteristic vectors were obtained and classified with standard neural networks. A training and testing set of positive and negative vectors were compiled. Vectors obtained from a single patient were included only in the testing or in the training set, but never in both. Our approach was able to correctly classify vectors with evidence of pneumonia, with 91.5% sensitivity and 100% specificity.

AB - Pneumonia is one of the major causes of child mortality. Unfortunately, in developing countries there is a lack of infrastructure and medical experts in rural areas to provide the required diagnostics opportunely. Lung ultrasound echography has proved to be an important tool to detect lung consolidates as evidence of pneumonia. This paper presents a method for automatic diagnostics of pneumonia using ultrasound imaging of the lungs. The approach presented here is based on the analysis of patterns present in rectangular segments from the ultrasound digital images. Specific features from the characteristic vectors were obtained and classified with standard neural networks. A training and testing set of positive and negative vectors were compiled. Vectors obtained from a single patient were included only in the testing or in the training set, but never in both. Our approach was able to correctly classify vectors with evidence of pneumonia, with 91.5% sensitivity and 100% specificity.

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Automatic detection of pneumonia analyzing ultrasound digital images

Abstract

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Keywords

ASJC Scopus subject areas

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