The Automatic Detection of Pulmonary Nodules on Computed Tomography Images: A Novel Approach
Published 2022-03-03
Keywords
- Computer Tomography Image, HMM, Lung Nodule Segmentation, Wiener filter , Computer Aided Diagnosis.
Abstract
In the past eras, an immense deal of research work has been dedicated to the development of systems that could increase radiologists’ accuracy in detecting the lung nodules. In spite of the huge efforts, the difficulty is still open. This paper describes a methodology for automatic detection of lung nodules from Computed Tomography images. Computed Tomography (CT) is the most responsive imaging technique for detecting lung nodules, and currently being estimated as a screening tool for lung cancer in a large number of trials, calculated all over the world. Most medical analysis systems are founded on vast quantities of training data and take longer processing time. So for reducing these problems a medical diagnosis system based on Hidden Markov Model is presented. This automation process reduces the processing time and increases the diagnosis confidence.