Title :
A Multi-Classifier System for Pulmonary Nodule Classification
Author :
Antonelli, Michela ; Cococcioni, Marco ; Lazzerini, Beatrice ; Marcelloni, Francesco ; Stefanescu, Dan
Author_Institution :
Dept. of Inf. Eng., Univ. of Pisa, Pisa
Abstract :
We have developed a multi-classifier system for automatic classification of pulmonary nodules in lung CT (Computed Tomography) images. The system consists of a set of independent modules, each emulating a radiologist of a team, and a further module aimed at appropriately combining theradiologists´ opinions. In the experiments we obtained a sensitivity of 95% against a specificity of 91.33%, adopting a combiner based on the decisio.n templates technique.
Keywords :
computerised tomography; image classification; lung; radiology; lung computed tomography images; multiclassifier system; pulmonary nodule classification; theradiologists; Biomedical imaging; Cancer detection; Classification tree analysis; Computed tomography; Costs; Lungs; Medical diagnostic imaging; Open wireless architecture; Phase detection; Testing; Nodule diagnosis; computer-aided diagnosis system; decision fusion; multi-classifier system;
Conference_Titel :
Computer-Based Medical Systems, 2008. CBMS '08. 21st IEEE International Symposium on
Conference_Location :
Jyvaskyla
Print_ISBN :
978-0-7695-3165-6
DOI :
10.1109/CBMS.2008.70
