Design of a Graph-Based System for Similar Case Retrieval of Pulmonary Nodules.
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.
University Hospital (HUPAA/EBSERH), Institute of Computing, Federal University of Alagoas, Maceió, Alagoas, Brazil.
José
J
Raniery Ferreira Junior
University Hospital (HUPAA/EBSERH), Institute of Computing, Federal University of Alagoas, Maceió, Alagoas, Brazil.
Marcelo
M
Costa Oliveira
Internal Medicine Department, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil.
Paulo
P
Mazzoncini de Azevedo-Marques
D003196:Computer Graphics; D057225:Data Mining / Q000379:methods; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D011873:Radiology Information Systems / Q000458:organization & administration*; D012985:Software Design; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014584:User-Computer Interface