An algorithm for feature extraction and detection of pulmonary nodules in digital radiographic images

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Resumen

This work proposes a method for feature extraction and detection of pulmonary nodules in digital radiographic images, as little visualization and highlighting of these features often prevent a deeper diagnosis in chest radiographs. The proposed method involves digital image processing techniques such as re-quantization, gamma correction, OTSU thresholding, projection analysis, convergence filter, dilation, erosion and geometric filters. The proposed algorithm has a sensitivity of 91%, specificity of 96% and precision 94% with a referential database of 50 chest radiographs.

Idioma originalInglés
Título de la publicación alojadaIEEE ICA-ACCA 2018 - IEEE International Conference on Automation/23rd Congress of the Chilean Association of Automatic Control
Subtítulo de la publicación alojadaTowards an Industry 4.0 - Proceedings
EditoresCristian Duran-Faundez, Gaston Lefranc, Mario Fernandez-Fernandez, Carlos Munoz, Ernesto Rubio
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781538655863
DOI
EstadoPublicada - 2 jul. 2018
Publicado de forma externa
EventoIEEE International Conference on Automation/23rd Congress of the Chilean Association of Automatic Control: Towards an Industry 4.0, ICA-ACCA 2018 - Greater Concepcion, Chile
Duración: 17 oct. 201819 oct. 2018

Serie de la publicación

NombreIEEE ICA-ACCA 2018 - IEEE International Conference on Automation/23rd Congress of the Chilean Association of Automatic Control: Towards an Industry 4.0 - Proceedings

Conferencia

ConferenciaIEEE International Conference on Automation/23rd Congress of the Chilean Association of Automatic Control: Towards an Industry 4.0, ICA-ACCA 2018
País/TerritorioChile
CiudadGreater Concepcion
Período17/10/1819/10/18

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