Lung Tumor Staging and Classification with Machine Learning and Deep Learning Models

Abstract In today’s worldwide health scenario, Lung Cancer has the highest rates of mortality and morbidity. The accurate and clinical staging of lung cancer category can effectively reduce the death rate, since the treatment phase requires the specific stage of cancer. However, the staging of lung cancer still remains challenging, requires more efforts. The Computed Tomography images (CT) images are utilized for the Computer Aided Diagnosis based cancer diagnosis. With that note, this paper develops a Volumetric Analysis for Lung Tumor Staging and Classification (VA-LTSC), in which the stages are classified based on Tumor Nodule Metastasis (TNM) with Machine Learning and Deep Learning Models Moreover, the proposed model comprises different phases. The results are measured using inputs from LIDC-IDRI and LUNA 16, based on classification accuracy, model effectiveness and time complexities and in all, the proposed model outperforms the existing results.