Certain investigation on machine learning based approach for screening of chronic obstructive pulmonary disease from chest computed tomography scans with advanced filtering techniques

Abstract

Medical imaging is one of the most useful diagnostic tools available Chronic Obstructive Pulmonary Disease COPD is the name for a group of lung diseases including chronic bronchitis emphysema and chronic obstructive airways disease Chest Computed Tomography CT scan provides additional information and it provides more detailed images of parts of the body that cannot easily be seen on a standard chest radiograph However the automatic screening process has a lot of advantages such as decreasing labour enhancing the sensitivity of the test and better precision in diagnosis by increasing the images that can be analyzed by the computer newlineThe present research deals with the three phases to screen the COPD disease from the chest CT scans Of the three phases the present research concentrates mainly on preprocessing and feature extraction For that three efficient novel techniques are proposed in the present research They are given as An Efficient Extreme Learning Machine ELM based Approach for the screening of COPD from Chest CT Scans with Laplacian Gaussian Filtering, Fuzzy Rule Based FRB Classifier Approach for Screening of COPD from Chest CT Scans with Median Filtering and Optimized Adaptive Neuro Fuzzy Inference System ANFIS Classifier Approach for the screening of COPD from Chest CT Scans with Adaptive Median Filtering newline newline newline