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dc.contributor.authorContreras Ojeda, Sara
dc.contributor.authorDomínguez Jiménez, Juan Antonio
dc.contributor.authorContreras Ortiz, Sonia Helena
dc.identifier.citationS. L. Contreras-Ojeda, J. A. Dominguez-Jiménez, and S. H. Contreras-Ortiz "Analysis and classification of lung and muscular tissues in ultrasound images using 2D wavelet transform and machine learning", Proc. SPIE 11583, 16th International Symposium on Medical Information Processing and Analysis, 115830F (3 November 2020);
dc.description.abstractUltrasound has been considered a safe and accurate alternative to radiography and computerized tomography to diagnose lung diseases such as pneumonia. However, speckle noise, artifacts or certain conditions can difficult image interpretation. For example, in some cases, the pleura line cannot be observed. This work proposes an approach for discriminating between lung and muscular tissues in ultrasound images. We evaluated the symlet and daubechies wavelets for feature extraction, principal component analysis and recursive backward elimination for feature selection, and supervised learning methods for classification. Statistical moments and the energy of the second horizontal coefficient and peak-to-peak root mean squared ratio were the features more outstanding over the rest. The best model was obtained with recursive backward elimination for feature selection and knearest neighbor for classification. Tissue classification was possible with a mean accuracy of 97.5% and area under the curve of 99%. These results offer great insights on the recognition of lung and muscular tissues, which could improve the effectiveness of automatic segmentation and analysis
dc.format.extent7 páginas
dc.sourceProceedings Volume 11583, 16th International Symposium on Medical Information Processing and Analysis; 115830F (2020)spa
dc.titleAnalysis and classification of lung and muscular tissues in ultrasound images using 2D wavelet transform and machine learningspa
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dc.subject.keywordsBiological organsspa
dc.subject.keywordsComputerized tomographyspa
dc.subject.keywordsDiscrete wavelet transformsspa
dc.subject.keywordsFeature extractionspa
dc.subject.keywordsImage classificationspa
dc.subject.keywordsMachine learningspa
dc.subject.keywordsNearest neighbor searchspa
dc.identifier.instnameUniversidad Tecnológica de Bolívarspa
dc.identifier.reponameRepositorio Universidad Tecnológica de Bolívarspa
dc.publisher.placeCartagena de Indiasspa

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Universidad Tecnológica de Bolívar - 2017 Institución de Educación Superior sujeta a inspección y vigilancia por el Ministerio de Educación Nacional. Resolución No 961 del 26 de octubre de 1970 a través de la cual la Gobernación de Bolívar otorga la Personería Jurídica a la Universidad Tecnológica de Bolívar.