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Using multi-layer perceptron with Laplacian edge detector for bladder cancer diagnosis

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 LearningConvolutional 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 Laplacianedge detector are achievingAUCvalue up to 0.99. When different image sizes are compared it can be seen that the best results are achieved if×5050and×100 100images were used.

Artificial intelligence ; Image pre-processing ; Laplacian edge detector ; Multi-layer perceptron ; Urinary bladder cancer

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