An explorative childhood pneumonia analysis based on ultrasonic imaging texture features

Omar Zenteno, Kristians Diaz, Roberto Lavarello, Mirko Zimic, Malena Correa, Holger Mayta, Cynthia Anticona, Monica Pajuelo, Richard Oberhelman, William Checkley, Robert H. Gilman, Dante Figueroa, Benjamín Castañeda

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

4 Citas (Scopus)


According to World Health Organization, pneumonia is the respiratory disease with the highest pediatric mortality rate accounting for 15% of all deaths of children under 5 years old worldwide. The diagnosis of pneumonia is commonly made by clinical criteria with support from ancillary studies and also laboratory findings. Chest imaging is commonly done with chest X-rays and occasionally with a chest CT scan. Lung ultrasound is a promising alternative for chest imaging; however, interpretation is subjective and requires adequate training. In the present work, a two-class classification algorithm based on four Gray-level co-occurrence matrix texture features (i.e., Contrast, Correlation, Energy and Homogeneity) extracted from lung ultrasound images from children aged between six months and five years is presented. Ultrasound data was collected using a L14-5/38 linear transducer. The data consisted of 22 positive-and 68 negative-diagnosed B-mode cine-loops selected by a medical expert and captured in the facilities of the Instituto Nacional de Salud del Ninõ (Lima, Peru), for a total number of 90 videos obtained from twelve children diagnosed with pneumonia. The classification capacity of each feature was explored independently and the optimal threshold was selected by a receiver operator characteristic (ROC) curve analysis. In addition, a principal component analysis was performed to evaluate the combined performance of all the features. Contrast and correlation resulted the two more significant features. The classification performance of these two features by principal components was evaluated. The results revealed 82% sensitivity, 76% specificity, 78% accuracy and 0.85 area under the ROC.

Idioma originalInglés
Título de la publicación alojada11th International Symposium on Medical Information Processing and Analysis
EditoresJuan D. Garcia-Arteaga, Jorge Brieva, Natasha Lepore, Eduardo Romero
ISBN (versión digital)9781628419160
EstadoPublicada - 2015
Evento11th International Symposium on Medical Information Processing and Analysis, SIPAIM 2015 - Cuenca, Ecuador
Duración: 17 nov. 201519 nov. 2015

Serie de la publicación

NombreProceedings of SPIE - The International Society for Optical Engineering
ISSN (versión impresa)0277-786X
ISSN (versión digital)1996-756X


Conferencia11th International Symposium on Medical Information Processing and Analysis, SIPAIM 2015


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