## 2 Materials and Methods  
### Database  
The development of a CAD system is intimately linked to a data collection. In this work the dataset provided by the AIDA (AutoImmunite, Diagnostic Assiste par ordinateur) project [24] was used. In this project, using a uniform approach, seven immunology services (three Tunisian and four Sicilian) contributed to collect images of the IIF test on HEp-2 cells. These images corresponded to the routine IIF technique performed in different hospitals for an autoimmune disease diagnosis and were, thus, reported by senior immunologists. Each image and related report was stored in a common database created in the project. Manufacturers of kits and instruments employed for the ANA testing were different site-to-site; the following automated systems solution for the processing of Indirect Immunofluorescence tests have been used--IF Sprinter from Euroimmun, NOVA from INOVA diagnostic, and Helios from Aesku. They were used to carry out the serial dilutions and a dilution of 1/80 was considered to be positive. The images had 24 bits color-depth and were stored in the common image file formats. The database acquired during the AIDA project consisted of two parts--one part was public, the other was private.  
The public \"AIDA_HEp-2\" Database was a subset of the full AIDA database, where three physician experts(independently) have expressed a unanimous opinion when reporting. This is available to the scientific community and, to our knowledge, it is the largest HEp-2 images public database that is most representative of real cases, including a variety of single and multiple patterns; 2080 images for which there is a triple concordance of reports.  
The database contains fluorescence positive sera with a variety of more-than-twenty staining patterns. In each image a single or multiple pattern can be present. The patterns terminology is in accordance with the \"International Consensus on ANA Patterns\" (ICAP): \"www.anapatterns.org\" [26].  
The public part of the AIDA Database consists of 2080 images, composed as follows: 998 patients (261 males, 737 females), 1498 images show positive fluorescence intensity, 582 show negative, 479 refer to males and 1601 to females. Among the images with positive fluorescence, those relating to patterns belonging to the six typologies object of the present research are a total of 220, their distribution is shown in Figure 2. The public database can be downloaded, after registration, from the download section of the AIDA project site ([[http://www.aidaproject.net/downloads](http://www.aidaproject.net/downloads)]([http://www.aidaproject.net/downloads](http://www.aidaproject.net/downloads))).  
The private part of the AIDA Database is structured in the same way as the public part, and it has about 20,000 positive and negative images. However, among all these images only about 3000 have triple concordance of reports. This part of the AIDA database is only accessible to the partners who participated in the project.  
The system proposed here has been trained and optimized on the private part and tested on the public part of the AIDA database. In the training-tuning phase, in order to make the best use of the data, the leave-one-specimen-out cross-validation technique have been used. This method consists of leaving out one specimen, rather than leaving out a single image (or a single cell) for the construction of the training set; images of the same specimen, belonging to the same patient, are similar (in terms of the average intensity and contrast) and introduce bias. The specimen left out is used for validation. Regarding the analysis of fluorescence intensity, as in this case, the wells at our disposal were statistically much greater; during training-tuning we proceeded with a leave-ten-specimens-out (i.e., leaving out ten specimen).