Computerized Analysis of Classification of Lung Nodules and Comparison between Homogeneous and Heterogeneous Ensemble of Classifier Model

In this paper, we convert multi class subjective ratings for lung nodules from radiologists to binary class problem and use that to classify. We also evaluate the difference in performance between homogenous and heterogeneous ensemble of classifiers. We have used radiologist's characteristic ratings for nodule as subjective feature and extracted 54 low level image features. Instead of predicting nodule characteristic we have used the ground truth provided by radiologists and converted the problem into binary class. Results show that the proposed heterogeneous ensemble classifier model works better than the previous traditional models.