Computer-Aided Diagnosis of Lung Nodules in Computed Tomography by Using Phylogenetic Diversity, Genetic Algorithm, and SVM

Journal of Digital Imaging
Antonio Oseas de Carvalho FilhoMarcelo Gattass

Abstract

Lung cancer is pointed as the major cause of death among patients with cancer throughout the world. This work is intended to develop a methodology for diagnosis of lung nodules using images from the Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI). The proposed methodology uses image processing and pattern recognition techniques. In order to differentiate between the patterns of malignant and benign nodules, we used phylogenetic diversity by means of particular indexes, that are: intensive quadratic entropy, extensive quadratic entropy, average taxonomic distinctness, total taxonomic distinctness, and pure diversity indexes. After that, we applied the genetic algorithm for selection of the best model. In the tests' stage, we applied the proposed methodology to 1405 (394 malignant and 1011 benign) nodules. The proposed work presents promising results at the classification into malignant and benign, achieving accuracy of 92.52%, sensitivity of 93.1% and specificity of 92.26%. The results demonstrated a good rate of correct detections using texture features. Since a precocious detection allows a faster therapeutic intervention, thus a more favorable prognostic to the patient, we propose herein a methodo...Continue Reading

References

Jul 29, 1994·Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences·D P Faith
Jun 25, 1998·European Journal of Radiology·A R van Erkel, P M Pattynama
Mar 17, 2001·JAMA : the Journal of the American Medical Association·M K GouldD K Owens
Feb 21, 2002·Proceedings of the National Academy of Sciences of the United States of America·Wes SechrestJohn L Gittleman
Jun 20, 2003·The New England Journal of Medicine·David OstSteven H Feinsilver
Apr 4, 2006·Proceedings of the National Academy of Sciences of the United States of America·Sharon Y StraussNicolas Salamin
Jan 16, 2008·Radiology·David M HansellJacques Remy
Jun 21, 2008·Oecologia·Oliver SchweigerIngolf Kühn
Jun 17, 2009·IEEE Transactions on Bio-medical Engineering·Xujiong YeGareth Beddoe
Jan 5, 2011·Frontiers in Bioscience (Landmark Edition)·Wenshu ChenYong Lin
Mar 9, 2012·The New England Journal of Medicine·Marco GerlingerCharles Swanton
Oct 2, 2012·Computers in Biology and Medicine·Stelmo Magalhães Barros NettoMarcelo Gattass
Sep 17, 2013·Diagnostic and Interventional Imaging·M LederlinF Laurent
Dec 18, 2013·Artificial Intelligence in Medicine·Antonio Oseas de Carvalho FilhoMarcelo Gattass
Jul 7, 2014·Seminars in Diagnostic Pathology·Shekhar S PatilEdith M Marom
Sep 23, 2014·Seminars in Diagnostic Pathology·Junya Fujimoto, Ignacio I Wistuba

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