Convolutional neural network based ResNet50 for finding accuracy in prediction of lung cancer using CT images and compared with CNN based inception V3
Navneeth Krishna, R. Puviarasi, R. Puviarasi · AIP conference proceedings · 2024
To find and compare the accuracy in prediction of lung cancer using ResNet-50 and Inception V3. Materials and methods: The CT images with two classes (diseased/normal) are taken.The dataset related to our work is collected from the Iraq-Oncology Teaching Hospital/National Center for Cancer Diseases.Convolution Neural Network (CNN) based ResNet50 and Inception V3 methods are the two groups with sample size of 989 in each with Gpower (80%).Results: The proposed model ResNet50 produced improved accuracy of (0.93094±0.057554%)than Inception-V3(0.69938±0.138030)with the significance value of <0.05.Conclusion: ResNet50 produced high accuracy (%) results compared with CNN-Inceptionv3 model.