Publicación:
Automatic classification of pediatric pneumonia based on lung ultrasound pattern recognition
Automatic classification of pediatric pneumonia based on lung ultrasound pattern recognition
No hay miniatura disponible
Fecha
2018
Autores
Correa M.
Zimic M.
Barrientos F.
Barrientos R.
Román-Gonzalez A.
Pajuelo M.J.
Anticona C.
Mayta H.
Alva A.
Solis-Vasquez L.
Título de la revista
Revista ISSN
Título del volumen
Editor
Public Library of Science
Proyectos de investigación
Unidades organizativas
Número de la revista
Abstracto
Pneumonia is one of the major causes of child mortality, yet with a timely diagnosis, it is usually curable with antibiotic therapy. In many developing regions, diagnosing pneumonia remains a challenge, due to shortages of medical resources. Lung ultrasound has proved to be a useful tool to detect lung consolidation as evidence of pneumonia. However, diagnosis of pneumonia by ultrasound has limitations: it is operator-dependent, and it needs to be carried out and interpreted by trained personnel. Pattern recognition and image analysis is a potential tool to enable automatic diagnosis of pneumonia consolidation without requiring an expert analyst. This paper presents a method for automatic classification of pneumonia using ultrasound imaging of the lungs and pattern recognition.
Descripción
Palabras clave
male,
Article,
artificial neural network,
automation,
child,
clinical article,
controlled study,
digital imaging,
disease classification,
echography,
female,
human,
image analysis,
image processing,
infant,
lung infiltrate