Using VGG16 Algorithms for classification of lung cancer in CT scans
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Hasan Hejbari Zargar Saha Hejbari Zargar Raziye Mehri Farzane Tajidini
Lung cancer is the leading reason behind cancer-related deaths within the
world. Early detection of lung nodules is vital for increasing the survival
rate of cancer patients. Traditionally, physicians should manually identify the
world suspected of getting carcinoma. When developing these detection systems,
the arbitrariness of lung nodules' shape, size, and texture could be a
challenge. Many studies showed the applied of computer vision algorithms to
accurate diagnosis and classification of lung nodules. A deep learning
algorithm called the VGG16 was developed during this paper to help medical
professionals diagnose and classify carcinoma nodules. VGG16 can classify
medical images of carcinoma in malignant, benign, and healthy patients. This
paper showed that nodule detection using this single neural network had 92.08%
sensitivity, 91% accuracy, and an AUC of 93%.