Filtering of the skin portion on lung ultrasound digital images to facilitate automatic diagnostics of pneumonia

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

doi:10.1109/CONCAPAN.2016.7942376

Filtering of the skin portion on lung ultrasound digital images to facilitate automatic diagnostics of pneumonia

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

Bloomberg School of Public Health

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

2 Scopus citations

Abstract

Pneumonia is one of the major causes of child mortality, but it is curable if one can achieves early diagnostics. 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. The use of ultrasound to detect pneumonia is limited by the image analysis for interpretation, which is carried by human experts. Pattern recognition and image analysis is a potential tool to facilitate recognition of pneumonia consolidates in absence of medical experts for automatic diagnostics. To perform an automatic analysis of lung ultrasound images for pneumonia detection, the noise introduced by the image portion of the skin, notably complicates the processing and interpretation. This paper presents a methodology to recognize and eliminate the portion of the skin in lung ultrasound images.

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.2016.7942376
State	Published - Jul 2 2016
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

Ultrasound images
echography
image processing
remote diagnostics

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.2016.7942376

Cite this

Barrientos, F., Roman-Gonzalez, A., Barrientos, R., Solis, L., Alva, A., Correa, M., Pajuelo, M., Anticona, C., Lavarello, R., Castaneda, B., Oberhelman, R., Gilman, R. H., & Zimic, M. (2016). Filtering of the skin portion on lung ultrasound digital images to facilitate automatic diagnostics of pneumonia. In 2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016 Article 7942376 (2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CONCAPAN.2016.7942376

Filtering of the skin portion on lung ultrasound digital images to facilitate automatic diagnostics of pneumonia. / Barrientos, Franklin; Roman-Gonzalez, Avid; Barrientos, Ronald et al.
2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7942376 (2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016).

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

Barrientos, F, Roman-Gonzalez, A, Barrientos, R, Solis, L, Alva, A, Correa, M, Pajuelo, M, Anticona, C, Lavarello, R, Castaneda, B, Oberhelman, R, Gilman, RH & Zimic, M 2016, Filtering of the skin portion on lung ultrasound digital images to facilitate automatic diagnostics of pneumonia. in 2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016., 7942376, 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.2016.7942376

Barrientos F, Roman-Gonzalez A, Barrientos R, Solis L, Alva A, Correa M et al. Filtering of the skin portion on lung ultrasound digital images to facilitate automatic diagnostics of pneumonia. In 2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016. Institute of Electrical and Electronics Engineers Inc. 2016. 7942376. (2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016). doi: 10.1109/CONCAPAN.2016.7942376

Barrientos, Franklin ; Roman-Gonzalez, Avid ; Barrientos, Ronald et al. / Filtering of the skin portion on lung ultrasound digital images to facilitate automatic diagnostics of pneumonia. 2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016. Institute of Electrical and Electronics Engineers Inc., 2016. (2016 IEEE 36th Central American and Panama Convention, CONCAPAN 2016).

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AU - Correa, Malena

AU - Pajuelo, Monica

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AU - Lavarello, Roberto

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AB - Pneumonia is one of the major causes of child mortality, but it is curable if one can achieves early diagnostics. 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. The use of ultrasound to detect pneumonia is limited by the image analysis for interpretation, which is carried by human experts. Pattern recognition and image analysis is a potential tool to facilitate recognition of pneumonia consolidates in absence of medical experts for automatic diagnostics. To perform an automatic analysis of lung ultrasound images for pneumonia detection, the noise introduced by the image portion of the skin, notably complicates the processing and interpretation. This paper presents a methodology to recognize and eliminate the portion of the skin in lung ultrasound images.

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Filtering of the skin portion on lung ultrasound digital images to facilitate automatic diagnostics of pneumonia

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Keywords

ASJC Scopus subject areas

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