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Diagnostics
Volume 11
Issue 3
10.3390/diagnostics11030451
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Article

The Role in Teledermoscopy of an Inexpensive and Easy-to-Use Smartphone Device for the Classification of Three Types of Skin Lesions Using Convolutional Neural Networks

by
Federica Veronese
1,*,
Francesco Branciforti
2,
Elisa Zavattaro
3,*,
Vanessa Tarantino
4,
Valentina Romano
4,
Kristen M. Meiburger
2,
Massimo Salvi
2,
Silvia Seoni
2 and
Paola Savoia
4
1
AOU Maggiore della Carità, C.so Mazzini 18, 28100 Novara, Italy
2
Biolab, PolitoBIOmedLab, Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy
3
Department of Translational Medicine, University of Eastern Piedmont, Via Solaroli 17, 28100 Novara, Italy
4
Department of Health Science, University of Eastern Piedmont, Via Solaroli 17, 28100 Novara, Italy
*
Authors to whom correspondence should be addressed.
Academic Editor: Chyi-Chia Richard Lee
Diagnostics 2021, 11(3), 451; https://doi.org/10.3390/diagnostics11030451
Received: 11 February 2021 / Revised: 25 February 2021 / Accepted: 3 March 2021 / Published: 5 March 2021
(This article belongs to the Special Issue Imaging Diagnosis for Melanoma)
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Abstract

Background. The use of teledermatology has spread over the last years, especially during the recent SARS-Cov-2 pandemic. Teledermoscopy, an extension of teledermatology, consists of consulting dermoscopic images, also transmitted through smartphones, to remotely diagnose skin tumors or other dermatological diseases. The purpose of this work was to verify the diagnostic validity of images acquired with an inexpensive smartphone microscope (NurugoTM), employing convolutional neural networks (CNN) to classify malignant melanoma (MM), melanocytic nevus (MN), and seborrheic keratosis (SK). Methods. The CNN, trained with 600 dermatoscopic images from the ISIC (International Skin Imaging Collaboration) archive, was tested on three test sets: ISIC images, images acquired with the NurugoTM, and images acquired with a conventional dermatoscope. Results. The results obtained, although with some limitations due to the smartphone device and small data set, were encouraging, showing comparable results to the clinical dermatoscope and up to 80% accuracy (out of 10 images, two were misclassified) using the NurugoTM demonstrating how an amateur device can be used with reasonable levels of diagnostic accuracy. Conclusion. Considering the low cost and the ease of use, the NurugoTM device could be a useful tool for general practitioners (GPs) to perform the first triage of skin lesions, aiding the selection of lesions that require a face-to-face consultation with dermatologists. View Full-Text
Keywords: telemedicine; teledermoscopy; convolutional neural networks telemedicine; teledermoscopy; convolutional neural networks
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MDPI and ACS Style

Veronese, F.; Branciforti, F.; Zavattaro, E.; Tarantino, V.; Romano, V.; Meiburger, K.M.; Salvi, M.; Seoni, S.; Savoia, P. The Role in Teledermoscopy of an Inexpensive and Easy-to-Use Smartphone Device for the Classification of Three Types of Skin Lesions Using Convolutional Neural Networks. Diagnostics 2021, 11, 451. https://doi.org/10.3390/diagnostics11030451

AMA Style

Veronese F, Branciforti F, Zavattaro E, Tarantino V, Romano V, Meiburger KM, Salvi M, Seoni S, Savoia P. The Role in Teledermoscopy of an Inexpensive and Easy-to-Use Smartphone Device for the Classification of Three Types of Skin Lesions Using Convolutional Neural Networks. Diagnostics. 2021; 11(3):451. https://doi.org/10.3390/diagnostics11030451

Chicago/Turabian Style

Veronese, Federica, Francesco Branciforti, Elisa Zavattaro, Vanessa Tarantino, Valentina Romano, Kristen M. Meiburger, Massimo Salvi, Silvia Seoni, and Paola Savoia. 2021. "The Role in Teledermoscopy of an Inexpensive and Easy-to-Use Smartphone Device for the Classification of Three Types of Skin Lesions Using Convolutional Neural Networks" Diagnostics 11, no. 3: 451. https://doi.org/10.3390/diagnostics11030451

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