A method for lung nodule visualization from multi-slice CT data

Abstract Visual detection of lung nodules in multi-slice computed tomography (MSCT) datasets is a tedious, time-consuming and error-prone procedure. For this reason, various computer assisted detection (CAD) systems for the automated detection of lung nodules have been presented in the literature. In this paper, we propose a complementary method helping in the visual detection of nodules. We suggest to segment the lung and the pulmonary vessel tree from the dataset. A maximum intensity projection (MIP) of the lung without the pulmonary vessel tree shows the nodules clearly. Rotating the MIP gives a visual impression of the density, size, shape and spatial position of the nodules.