Nasal cytology with deep learning techniques.
Journal:
International journal of medical informatics
PMID:
30623779
Abstract
BACKGROUND: In recent years, cytological observations in the Rhinology field are being increasingly utilized. This development has taken place over the last two decades and has proven to be fundamental in defining new nosological entities and in driving changes in the previous classification of rhinitis. The simplicity of the technique and its low invasiveness make nasal cytology a practical diagnostic tool for all rhino-allergology services. Furthermore, since it allows the monitoring of responses to treatment, this method plays an important role in guiding a more effective and less expensive diagnostic program. Microscopic observation requires prolonged effort by a specialist, but the modern scanning systems for cytological preparations and the new affordable digital microscopes allow to design a software support system, based on deep learning techniques, to relieve specialist's tiring activity.