A Novel Approach of Automatic Detection of Pulmonary Nodules on Computed Tomography Images

Abstract

Previously, a significant amount of research effort was devoted to the creation of technologies that may improve radiologists' accuracy in identifying lung nodules. Despite enormous efforts, the problem remains unsolved. This research offers a method for detecting lung nodules from computed tomography pictures automatically. CT is the most responsive imaging modality for identifying lung nodules, and it is now being evaluated as a lung cancer screening tool in a vast number of trials conducted across the world. Most medical analysis systems are based on large amounts of training data and require a long time to process. As a result, a medical diagnosis system based on the Hidden Markov Model is proposed in order to alleviate these issues. This automation shortens the processing time and improves the accuracy of the diagnosis.