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.
A multi-classifier system for pulmonary nodule classification
ANTONELLI, MICHELA;COCOCCIONI, MARCO;LAZZERINI, BEATRICE;MARCELLONI, FRANCESCO;
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.File in questo prodotto:
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