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 decision templates technique.
Titolo: | A multi-classifier system for pulmonary nodule classification |
Autori interni: | |
Anno del prodotto: | 2008 |
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 decision templates technique. |
Handle: | http://hdl.handle.net/11568/200510 |
ISBN: | 9780769531656 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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