Lung cancer presents the highest cause of death among patients around the world, in addition of being one of the smallest survival rates after diagnosis. In this paper, we exploit a deep learning technique jointly with the genetic algorithm to classify lung nodules in whether malignant or benign, without computing the shape and texture features. The methodology was tested on computed tomography (CT) images from the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), with the best sensitivity of 94.66%, specificity of 95.14%, accuracy of 94.78% and area under the ROC curve of 0.949.
Multimedia Tools and Applications – Springer Journals
Published: Mar 8, 2017
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