Development and Application in Clinical Routine of Computer Aided Detection (CAD) Algorithms for the Identification of Pulmonary Nodules

摘要

Lung Cancer is one of the main public health issues in developed countries, accounting for about 19% and 28% of cancer-related deaths in Europe (Ferlay et al., 2010) and the United States of America (Jemal et al., 2009), respectively, with a five-year survival rate of only 10-16% (Jemal et al., 2010). Computed Tomography (CT) has been shown to be the most sensitive imaging modality for the detection of small pulmonary nodules: low dose high resolution CT-based screening trials are regarded as a promising technique for detecting early-stage lung cancers (Team et al., 2011). The identification of early stage pathological Regions of Interests (ROIs) in low dose high resolution CT scans is a very difficult and time consuming task for radiologists, because of the large number (300/500) of noisy 2D slices to be analyzed.