Pulmonary nodule classification based on nodule retrieval from 3-D thoracic CT image database

Abstract

The purpose of this study is to develop an image-guided decision support system that assists decision-making in clinical differential diagnosis of pulmonary nodules. This approach retrieves and displays nodules that exhibit morphological and internal profiles consistent to the nodule in question. It uses a three-dimensional (3-D) CT image database of pulmonary nodules for which diagnosis is known. In order to build the system, there are following issues that should be solved, (1) to categorize the nodule database with respect to morphological and internal features, (2) to quickly search nodule images similar to an indeterminate nodule from a large database, and (3) to reveal malignancy likelihood computed by using similar nodule images. Especially, the first problem influences the design of other issues. The successful categorization of nodule pattern might lead physicians to find important cues that characterize benign and malignant nodules. This paper focuses on an approach to categorize the nodule database with respect to nodule shape and CT density patterns inside nodule. © Springer-Verlag Berlin Heidelberg 2004.