21st EANN 2020, 5 -7 June 2020, Greece

Identification of Eyelid Basal Cell Carcinoma using Artificial Neural Networks

Evangelos Georgios Chatzopoulos, George Anastassopoulos, ADAM ADAMOPOULOS, Efstathios Detorakis


  First results of the classification of the eyelid Basal Cell Carcinoma using Ar-tificial Neural Networks are presented. Full, or half-face photographs of healthy subjects and patients suffering from eyelid Basal Cell Carcinoma were used to train and validate Artificial Neural Networks for the purpose of pattern recognition, identification and classification The efficiency of the al-gorithm was tested using various training methods and it was evaluated using the accuracy score, that is, the ration of the number of the correctly classi-fied cases over the total number of cases under examination. With respect to the accuracy, the proposed algorithm reached up to 100% performance. The algorithm is accompanied by a specifically designed and developed user friendly Graphical User Interface.  

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