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

• Autores: 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.
• Formato: objeto de conferencia
• Fecha de Publicación: 2017
• Institución: Consejo Nacional de Ciencia Tecnología e Innovación
• Repositorio: CONCYTEC-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.concytec.gob.pe:20.500.12390/618
• Enlace del recurso: https://hdl.handle.net/20.500.12390/618; https://doi.org/10.1109/CONCAPAN.2016.7942376
• Nivel de acceso: acceso abierto
• Materia: Ultrasonic imaging; Biological organs; Developing countries; Diagnosis; Image processing; Medical imaging; Pattern recognition; Ultrasonic applications; Automatic analysis; Automatic diagnostics; Child mortality; https://purl.org/pe-repo/ocde/ford#3.01.00

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.