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Proposal of the CAD System for Melanoma Detection Using Reconfigurable Computing

Wysterlânya K. P. Barros, Daniel S. Morais, Felipe F. Lopes, Matheus Torquato Orcid Logo, Raquel de M. Barbosa, Marcelo A. C. Fernandes

Sensors, Volume: 20, Issue: 11, Start page: 3168

Swansea University Author: Matheus Torquato Orcid Logo

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DOI (Published version): 10.3390/s20113168

Abstract

This work proposes dedicated hardware to real-time cancer detection using Field-Programmable Gate Arrays (FPGA). The presented hardware combines a Multilayer Perceptron (MLP) Artificial Neural Networks (ANN) with Digital Image Processing (DIP) techniques. The DIP techniques are used to extract the f...

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Published in: Sensors
ISSN: 1424-8220
Published: MDPI AG 2020
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa54469
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Abstract: This work proposes dedicated hardware to real-time cancer detection using Field-Programmable Gate Arrays (FPGA). The presented hardware combines a Multilayer Perceptron (MLP) Artificial Neural Networks (ANN) with Digital Image Processing (DIP) techniques. The DIP techniques are used to extract the features from the analyzed skin, and the MLP classifies the lesion into melanoma or non-melanoma. The classification results are validated with an open-access database. Finally, analysis regarding execution time, hardware resources usage, and power consumption are performed. The results obtained through this analysis are then compared to an equivalent software implementation embedded in an ARM A9 microprocessor.
Keywords: artificial neural networks; digital image processing; melanoma detection
College: Faculty of Science and Engineering
Issue: 11
Start Page: 3168

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