Authors:
Paolo Soda
and
Giulio Iannello
Affiliation:
Facoltà di Ingegneria, Università Campus Bio-Medico di Roma, Italy
Keyword(s):
Computer Aided Diagnosis (CAD, Multiple Expert Systems, Classifier Aggregation, Medical Imaging, Indirect ImmunoFluorescence (IIF), HEp-2 Cell Classification.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Decision Support Systems
;
Expert Systems
;
Health Information Systems
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Symbolic Systems
Abstract:
In Indirect Immunofluorescence (IIF) the use of Computer-Aided Diagnosis (CAD) tools can support
physicians’ estimation of both fluorescence intensity and staining pattern. This paper reports our experiences in the staining pattern recognition of IIF wells. Since several cells constitute each well, we have developed a Multiple Expert System (MES) based on the one-per-class approach devised to classify the pattern of individual cells. As a novelty, we introduce an aggregation rule based on the estimation of the reliability of each composing experts. Then, the whole well staining pattern is computed using the reliability of its cells classification. The approach has been successfully tested on an annotated set of IIF images.