Proposal of the CAD System for Melanoma Detection Using Reconfigurable Computing.

Autor: Barros WKP; Laboratory of Machine Learning and Intelligent Instrumentation, Federal University of Rio Grande do Norte, Natal, RN 59078-970, Brazil., Morais DS; Laboratory of Machine Learning and Intelligent Instrumentation, Federal University of Rio Grande do Norte, Natal, RN 59078-970, Brazil., Lopes FF; Laboratory of Machine Learning and Intelligent Instrumentation, Federal University of Rio Grande do Norte, Natal, RN 59078-970, Brazil., Torquato MF; College of Engineering, Swansea University, Swansea, Wales SA2 8PP, UK., Barbosa RM; Laboratory of Drug Development, Department of Pharmacy, Federal University of Rio Grande do Norte, Natal, RN 59078-970, Brazil., Fernandes MAC; Laboratory of Machine Learning and Intelligent Instrumentation, Federal University of Rio Grande do Norte, Natal, RN 59078-970, Brazil.; Department of Computer and Automation Engineering, Federal University of Rio Grande do Norte, Natal, RN 59078-970, Brazil.
Jazyk: angličtina
Zdroj: Sensors (Basel, Switzerland) [Sensors (Basel)] 2020 Jun 03; Vol. 20 (11). Date of Electronic Publication: 2020 Jun 03.
DOI: 10.3390/s20113168
Abstrakt: 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.
Databáze: MEDLINE
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