Summary
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.
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Badura, P., Piętka, E. (2008). Pre- and Postprocessing Stages in Fuzzy Connectedness-Based Lung Nodule CAD. In: Pietka, E., Kawa, J. (eds) Information Technologies in Biomedicine. Advances in Soft Computing, vol 47. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68168-7_21
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DOI: https://doi.org/10.1007/978-3-540-68168-7_21
Publisher Name: Springer, Berlin, Heidelberg
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