Dynamic CNN: An Automatic Dynamic Model for Lung Cancer Lesion Detection

Lung cancer is one of the most deadly diseases in emergent world, and early discovery of lung cancer is challenging. The diagnosis and treatment of lung cancer has been one of the most difficult challenges people have faced in recent decades. Early detection of the tumour will consistently save a large number of lives worldwide. The current computer-aided detection techniques have a convoluted workflow and poor detection precision. This research addresses a novel measure for classifying lung tumours as malignant or harmful using Dynamic Convolutional Neural Networks (Dynamic CNN). The proposed Dynamic CNN model attained an accuracy of 96
^%
, which outperforms to other cutting-edge deep learning measures.