GA-SVM based lungs nodule detection and classification

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Abstract

In this paper we have proposed a method for lungs nodule detection from computed tomography (CT) scanned images by using Genetic Algorithms (GA) and morphological techniques. First of all, GA has been used for automated segmentation of lungs. Region of interests (ROIs) have been extracted by using 8 directional searches slice by slice and then features extraction have been performed. Finally SVM have been used to classify ROI that contain nodule. The proposed system is capable to perform fully automatic segmentation and nodule detection from CT Scan Lungs images. The technique was tested against the 50 datasets of different patients received from Aga Khan Medical University, Pakistan and Lung Image Database Consortium (LIDC) dataset. © 2009 Springer-Verlag Berlin Heidelberg.

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Jaffar, M. A., Hussain, A., Jabeen, F., Nazir, M., & Mirza, A. M. (2009). GA-SVM based lungs nodule detection and classification. In Communications in Computer and Information Science (Vol. 61, pp. 133–140). https://doi.org/10.1007/978-3-642-10546-3_17

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