# Performance of Fine-Tuning Convolutional Neural Networks for HEp-2 Image Classification
## 3 Materials and Methods  
### Database and Cross-Validation Strategy  
The analysis conducted in this work made use of the data contained in the public AIDA database [4]. Starting in November 2012, the Auto-Immunite, Diagnostic Assiste par ordinateur (AIDA) project is an international strategic project funded by the European Union (EU) in the context of ENPI Italy-Tunisia cross-border cooperation, in which one of the objectives was to collect a large database available to the scientific community.  
Using a standard approach, seven immunology services have collected images of the IIF test on HEp-2 cells accompanied by the report of the senior immunologists. The public AIDA database consists of images only where three physician experts (independently) have expressed a unanimous opinion when reporting.  
The AIDA database consists of 2080 images relating to 998 patients (261 males and 737 females); of these images, 582 are negative, while 1498 show a positive fluorescence intensity. The AIDA database is the public HEp-2 image database containing both images with positive fluorescence intensity and negative images; the other public databases are essentially composed of positive and weak positive fluorescence images, but not negative cases.  
Besides being \"numerous\", the database is extremely varied, containing fluorescence positive sera with a variety of more-than-twenty staining patterns. In each image, a single or multiple pattern can be present. The pattern terminology is in accordance with the _International Consensus on ANA Patterns (ICAP)_. Available online: [[http://www.anapatterns.org](http://www.anapatterns.org)]([http://www.anapatterns.org](http://www.anapatterns.org)) (accessed on 8 September 2020) [36]. Moreover, manufacturers of kits and instruments employed for the ANA testing were different site-to-site, as well as, different automated systems solutions for the processing of Indirect Immunofluorescence tests have been used: IF Sprinter Euroimmun, NOVA from INOVA diagnostic, and Helios from Aesku. HEp-2 images have been acquired, after incubation of the 1/80 serum dilution, by means of a unit consisting of a fluorescence microscope (40-fold magnification) coupled with a 50 W mercury vapor lamp and a digital camera. The camera has a CCD sensor equipped with pixel size that equals 3.2 \(\upmu\)m. The images have 24 bits color-depth and were stored in different common image file formats, as \"jpg\", \"png\", \"bmp\", and \"tif\". The public database can be downloaded, after registration, from the download section of the site AIDA Project. Available online: [[http://www.aidaproject.net/downloads](http://www.aidaproject.net/downloads)]([http://www.aidaproject.net/downloads](http://www.aidaproject.net/downloads)) (accessed on 8 September 2020).  
In order to make maximum use of the available data, the k-fold validation technique at the level of the specimen was used for the training-validation-test chain in this work [24]. In fact, in order not to affect the performance, the images belonging to the same well were used entirely, for training, or for testing. According to this method, the database was divided into five folds (k = 5), with this strategy, five trainings and related tests were carried out. Regarding the composition of the sets, approximately each training was obtained using 20% of the dataset for the test, while the remaining 80% was divided into training and validation to the extent of approximately 64% and 16% of the dataset.