Lung nodules detection and classification

Image processing techniques and computer aided diagnosis (CAD) systems have proved to be effective for the improvement of radiologists´ diagnosis. In this paper an automatic system detecting lung nodules from postero anterior chest radiographs is presented. The system extracts a set of candidate regions by applying to the radiograph three different and consecutive multi-scale schemes. The comparison of the results obtained with those presented in the literature show the efficacy of our multi-scale framework. Learning systems using as input different sets of features have been experimented for candidates classification, showing that support vector machines (SVMs) can be successfully applied for this task.