In this paper, the urinary bladder cancer diagnostic method which is based on Multi-Layer Perceptron and Laplacian edge detector is presented. The aim of this paper is to investigate the implementation possibility of a simpler method (Multi-Layer Perceptron) alongside commonly used methods, such as Deep Learning Convolutional Neural Networks, for the urinary bladder cancer detection. The dataset used for this research consisted of 1997 images of bladder cancer and 986 images of non-cancer tissue. The results of the conducted research showed that using Multi-Layer Perceptron trained and tested with images pre-processed with Laplacian edge detector are achieving AUC value up to 0.99. When different image sizes are compared it can be seen that the best results are achieved if 50×50 and 100×100 images were used.
Artificial intelligence in medicine. 2019 Nov 13 [Epub]
Ivan Lorencin, Nikola Anđelić, Josip Španjol, Zlatan Car
University of Rijeka, Faculty of Engineering, Vukovarska 58, 51000 Rijeka, Croatia., University of Rijeka, Faculty of Engineering, Vukovarska 58, 51000 Rijeka, Croatia. Electronic address: ., University of Rijeka, Faculty of Medicine, Braće Branchetta 20/1, 51000 Rijeka, Croatia; Clinical Hospital Center Rijeka, Krešimirova 42, 51000 Rijeka, Croatia.