ANALISIS CITRA CT SCAN KANKER PARU BERDASARKAN CIRI TEKSTUR GRAY LEVEL CO-OCCURRENCE MATRIX DAN CIRI MORFOLOGI MENGGUNAKAN JARINGAN SYARAF TIRUAN PROPAGASI BALIK

*Saitem Saitem  -  Departemen Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro, Semarang, Indonesia
Kuworo Adi  -  Departemen Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro, Semarang, Indonesia
Catur Edi Widodo  -  Departemen Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro, Semarang, Indonesia
Published: 1 Oct 2016.
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Abstract

The research about analysis of CT Scan image of lung cancer based on texture feature Gray Level Cooccurrence Matrix (GLCM) and morphological using neural network back propagation has been done. Lung cancer is cancer that general occurred in the word. In 2012, 1,8 million new cases lung cancer and 1,6 million mortality because lung cancer. The research aim to analysis CT Scan image of lung cancer based on texture feature Gray Level Co-occurrence Matrix (GLCM) and morphological using artificial neural network back propagation and calculated accuracy of testing artificial neural network back propagation. This research conducts pass through stages of segmentation, feature extraction and classfication. Texture and morphological feature extraction are obtained from the thresholding segmentation. The result of feature extraction are value contrast, correlation, energy, homogeneity and area ratio then used to input in process training and testing using neural network back propagation. Process training is conducts since 4 second with number of iteration 113 iteration. In proces training from 86 train data image, 85 image is able to classified, so acurracy of training up to 98,83% and in process testing from 57 test data, 56 test data is able to classified, so test accuracy value up to 98,24%.

Keywords: Lung cancer, CT Scan image, textured feature GLCM, Morphology feature, artificial neural network

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