Deep Learning: Theory, Architectures and Applications in Speech, Image and Language Processing

Deep Learning For Lung Cancer Detection

Author(s): Sushila Ratre*, Nehha Seetharaman and Aqib Ali Sayed

Pp: 47-59 (13)

DOI: 10.2174/9789815079210123010007

* (Excluding Mailing and Handling)

Abstract

By detecting lung cancer in advance, doctors can make the right decision to treat patients to ensure that they live long and healthy lives. This research aims to build a CNN model using a pre-trained model and functional API that would classify if a person had lung cancer or not based on a CT scan. This research uses CT scan images as input for the prediction model from the LUNA16 [Luna Nodule Analysis 2016] dataset for experimenting by using ResNet 50 and VGG 16. ResNet50 showed slightly high accuracy on test data compared to VGG16, which is 98%.

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