Searching similar images for classification of pulmonary nodules in three-dimensional CT images

This paper aims at obtaining diagnosis and prognosis information by searching similar images into a three-dimensional (3-D) CT image database of pulmonary nodules for which diagnosis is known. For this purpose, we propose an automatic method to retrieve nodule candidates with similar characteristics from the database. Each pulmonary nodule image is represented by the distribution pattern of CT density and 3-D curvature index. The nodule representation is then applied to a similarity measure such as a correlation coefficient. Our database is composed of 248 pulmonary nodules with associated clinical information. For each new case, we sort all the nodules of the database from most to less similar ones. Applying the retrieval method to our database, we present its feasibility to search the similar 3-D nodule images.