Analyzing CT Scan Images towards the Early Detection of Lung Cancer using Medical Images based Edge Feature Preserving CT Scan Medical Image Coder (EZWT - EFPIC)

Abstract

With the current improvements in virtual image processing techniques have received several benefits. Today, all of the scientific techniques produce virtual scientific pictures, through healthcare specialists analyze and diagnose the abnormality. The frequent view of scientific picture processing might also additionally appear simpler; however, it entails many challenges. As the scientific pics are interconnected with human lives, the laptop-aided scientific image processing structures have to be overcautious, if we want to eliminate inaccuracy rates. The utility of medical image processing techniques for the analysis of CT scan images similar to lung cancer cells has been gaining momentum in recent years. This paper discusses the use of a Transform Edge Feature preserving CT scan Medical Image Coder (EZWT - EFPIC) using Computed Tomography (CT) images to help in the early diagnosis of lung cancer. We discuss and explore the design and significance of an EZWT-EFPIC-CT image-processed model in cancer diagnosis.