Computerized characterization of contrast enhancement patterns for classifying pulmonary nodules

This paper presents a computerized classification scheme of pulmonary nodules in contrast enhanced dynamic CT images. Conventionally, we extracted 3-D nodule images by using a deformable surface model. However, there was a limit in segmenting the 3-D nodule images contacted with vessels and bronchi. In order to improve the segmentation accuracy of the 3-D nodule images, we developed a software tool to eliminate the leaked region of the 3-D nodule image due to vessels and bronchi interactively. Using our data set including 68 cases (28 benign and 40 malignant cases), we demonstrate how the segmentation accuracy affects the classification accuracy of our scheme.