Pre- and postprocessing stages in fuzzy connectedness-based lung nodule CAD

Abstract

The crucial part of the lung cancer computer-aided diagnosis (CAD) is the segmentation of pulmonary nodules in Computed Tomography (CT) study. A new multilevel approach based on fuzzy connectedness principles has been developed. The three-dimensional fuzzy connectedness analysis requires a dedicated preprocessing stage in order to limit the computation time to a reasonable range. It consists of the initial thresholding, connected components labeling, and creating the binary masks of regions within the thorax. For nodules connected to pleura or vessels, a separation step is needed, using mathematical morphology and the shape analysis. Separation of the nodule and pleura is performed in the preprocessing stage, whereas separation of a nodule and connected vessels -in the postprocessing stage. In this paper the methodology is described and illustrated. The whole segmentation method has been tested on a set of three-dimensional CT images of the thorax with delineated lung nodules. Results and some examples of such an application are shown. © 2008 Springer-Verlag Berlin Heidelberg.