Abstract
Pulmonary nodules with ground glass opacity (GGO) in lung CT images are difficult to differential diagnosis, and follow-up are often performed. In cases of follow-up, the present CT images are compared with past CT images, and it is necessary to evaluate the changes quantitatively. So, we have developed a volumetric segmentation algorithm of pulmonary nodules with GGO on CT images. Nodules with GGO, especially pure-GGO, are difficult to define a threshold value. Therefore, our algorithm does not define a threshold value. In our algorithm, the first step is to emphasize CT images using the sigmoid function. Next, the nodule is roughly segmented with background subtraction. Finally the nodule without vessels is decided by morphological operation, etc. For evaluation of our algorithm, we selected nodules with GGO from the dataset provided by LIDC (The Lung Image Database Consortium). In this paper, we illustrate some experimental result w hich applied our algorithm.
