engleski

Comparison of edge detectors for urinary bladder cancer diagnostic

One of the key challenges in urinary bladder cancer diagnosis is classification of tumor images without need of biopsy and pathohistological analysis. The convolutional neural network (CNN) is commonly used method in medical image classification. In this paper an alternative method to CNN is proposed. In this case, a multilayer perceptron is used alongside Sobel, Prewitt and Roberts edge detectors. By using Sobel edge detector, maximal AUC value of 0.99 is achieved. By using Prewitt and Roberts maximal AUC value of 0.98 is achieved. Results suggest that Prewitt edge detector offers stabile AUC vs. number of hidden layers performances.

Edge Detector ; Multilayer Perceptron ; Prewitt ; Roberts ; Sobel ; Urinary Bladder Cancer

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