Penerapan Metode Mobile-Net Untuk Klasifikasi Citra Penyakit Kanker Paru-Paru
DOI:
https://doi.org/10.30865/jurikom.v9i5.4918Keywords:
Lung Cancer, Segmentation, Classification, Mobile-Net, K-Means, CNNAbstract
Lung cancer is the main cause of all cancer diagnoses which reaches 13 percent in the world. According to WHO, lung cancer is the most common type of cancer in men in Indonesia and the fifth most common for all types of cancer in women. This is because the majority of smoking is experienced by men, causing lung cancer. Until now there is no suitable screening method for lung cancer in general. Screening methods that have been recommended for the detection of lung cancer are limited to high-risk patient groups. Whereas the risk of the severity of lung cancer will be even greater if it is not detected early, so as a result lung cancer patients are increasingly difficult to treat. The development of this biomedical technology can be used to assist the early detection process in patients suffering from lung cancer regardless of the criteria for the high risk group first, because if cancer is detected early, the death rate decreases. So in this study the researchers segmented and classified lung cancer using one of the architectures of the CNN algorithm, namely Mobile-Net to facilitate the classification and detection process of lung cancer. As the results of the research conducted by the author on the image of lung cancer with the K-Means segmentation process and classification using the CNN method with the Mobile-Net model, the accuracy is 96.70% and the validation accuracy is 90.45%. This shows that the classification using Mobile-Net with the segmentation process first on the lung cancer image can properly classify the type of disease well
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