Design of a Graph-Based System for Similar Case Retrieval of Pulmonary Nodules

Abstract

Due to difficulty of diagnosing lung cancer, it is important to integrate computational tools in the imaging interpretation process. Content-Based Image Retrieval (CBIR) can provide decision support to specialists by allowing them to find nodules from a database that are similar to a reference one. However, CBIR systems still face problems visualizing multidimensional images. This paper presents the design of a graph-based system for the retrieval of similar temporal computed tomography (CT) scans of pulmonary nodules, in order to optimize the visualization of multidimensional images in a CBIR system. Temporal Image Registration has been used to compare reference and retrieved previously segmented nodules. A rooted tree graph is employed to visualize retrieved cases, and it is deployed in a web system for portability and usability purposes.