Indirect immunofluorescence image classification using texture descriptors
Expert Systems with Applications: An International Journal
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Indirect immunofluorescence (IIF) is the recommended technique to detect rheumatic diseases through the analysis of images exhibiting a fluorescence in the green band. Since the request of such tests has recently increased, researches efforts have been directed towards the development of computer-aided diagnosis (CAD) tools supporting the specialists and improving the standardization of the method. Technological advances have made available color cameras for IIF image acquisition, but their use requires to determine which color to greyscale conversion method provides most useful information for the needs of CAD development. In this respect, we experimentally compare four different methods converting a color image into a greyscale one, analyzing wide features sets for each conversion method and applying four classification paradigms. Experiments have been carried out on an annotated dataset of HEp-2 cells, finding out a subset of features which is independent from the color model used and showing that a greyscale representation based on the HSI model better exploits information for IIF images analysis.