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WorldCist'18 - 6th World Conference on Information Systems and Technologies

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Blood cell classification using the Hough transform and convolutional neural networks

The detection of red blood cells in blood samples can be crucial for the disease detection in its early stages. The use of image processing techniques can accelerate and improve the effectiveness and efficiency of this detection. In this work, the use of the Circle Hough transform for cell detection and artificial neural networks for their identification as a red blood cell is proposed. Specifically, the application of neural networks (MLP) as a standard classification technique with (MLP) is compared with new proposals related to deep learning such as convolutional neural networks (CNNs). The different experiments carried out reveal the high classification ratio and show promising results after the application of the CNNs.

Miguel A. Molina-Cabello
University of Malaga
Spain

Ezequiel López-Rubio
University of Malaga
Spain

Rafael M. Luque-Baena
University of Malaga
Spain

María Jesús Rodríguez-Espinosa
University of Malaga
Spain

Karl Thurnhofer-Hemsi
University of Malaga
Spain

 

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