Taxonomic indexes for differentiating malignancy of lung nodules on CT images
Res. Biomed. Eng. (Online)
;
32(3): 263-272, July-Sept. 2016. tab, graf
Artigo
em Inglês
| LILACS
| ID: biblio-829487
ABSTRACT
Abstract Introduction Lung cancer remains the leading cause of cancer mortality worldwide, with one of the lowest survival rates after diagnosis. Therefore, early detection greatly increases the chances of improving patient survival. Methods This study proposes a method for diagnosis of lung nodules in benign and malignant tumors based on image processing and pattern recognition techniques. Taxonomic indexes and phylogenetic trees were used as texture descriptors, and a Support Vector Machine was used for classification. Results The proposed method shows promising results for accurate diagnosis of benign and malignant lung tumors, achieving an accuracy of 88.44%, sensitivity of 84.22%, specificity of 90.06% and area under the ROC curve of 0.8714. Conclusion The results demonstrate the promising performance of texture extraction techniques by means of taxonomic indexes combined with phylogenetic trees. The proposed method achieves results comparable to those previously published.
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DisponíveL
Índice:
LILACS (Américas)
Idioma:
Inglês
Revista:
Res. Biomed. Eng. (Online)
Assunto da revista:
Engenharia Biomdica
Ano de publicação:
2016
Tipo de documento:
Artigo
País de afiliação:
Brasil
Instituição/País de afiliação:
Universidade Federal do Maranhão/BR
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