## 1 Introduction  
Autoimmunity is the phenomenon for which the immune system activates its mechanisms towards molecules, cells, and structures of the same organism to which it belongs. The diseases caused by this phenomenon, which are defined as \"autoimmune\", are becoming increasingly widespread and include some of the most serious and penalizing conditions for the quality of life of those affected [1]. The diagnosis of autoimmune diseases is based on the finding of auto-antibodies, that is, antibodies directed against components of the same organism that produced them. Anti-nucleus antibodies (ANA) are a group of antibodies produced by the immune system that can mistakenly recognize the structures of the organism they belong to (autoantibodies). The ANA test identifies the presence of these autoantibodies in the blood. ANAs are the most recognized markers for the identification of an autoimmune process and, therefore, allow the exclusion of the presence of pathologies characterized by similar signs and symptoms. Positivity to the ANA test, tested by means of the Indirect ImmunoFluorescence (IIF) method, and performed by analyzing patterns and fluorescence intensity [2], is associated with multiple autoimmune diseases. The IIF test is particularly sensitive, but poorly specific. This is because ANA antibody titers tend to present themselves superior to the norm, in various non-pathological conditions. Furthermore, fluorescence intensity and fluorescence pattern analysis is particularly difficult, due to the similarity between different classes, and in any case is linked to the operator's experience [3]. The fluorescence pattern observed on the microscope (homogenous, speckled, nucleolar, cytoplasmic, centromere, nuclear dots, etc.) is specific, according to the nature of the self-antigen and its location in the cell. For these reasons, two senior immunologists (for double-reading) with strong experience in fluorescent image interpretation, are quite often needed. However this condition is not respected in all immunology laboratories involved in the diagnosis. The introduction of new modern approaches, based on computer systems, is an economic and effective support for the diagnosis of autoimmune diseases [4; 5]. Computer Aided Diagnosis (CAD) systems have been widely proposed in different areas of medicine and with different objectives, such as second-reading, improving the speed of the diagnostic processes, training physicians for special tasks, etc. [6; 7]. In recent years, the diagnostic support of CAD systems has been proposed for an automatic human epithelial type 2 (HEp-2) images classification. In this paper we describe a complete system (fluorescence intensity classification, image preprocessing, cell segmentation, cell classification, and image staining patterns classification), to support the autoimmune diagnostics in a HEp-2 image analysis. The system has been tested on a heterogeneous public database; heterogeneity comes from the geographical origins of the IIF images and the acquisition instrumentation adopted. This system is able to recognize six different patterns--homogenous, speckled, nucleolar, centromere, nuclear dots, and nuclear membrane. Figure 1 shows examples of each class.  
Figure 1: Examples of staining patterns in the IIF images; (**a**) homogenous; (**b**) speckled; (**c**) nucleolar; (**d**) centromere; (**e**) nuclear dots; (**f**) and nuclear membrane.