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

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.

Melanoma Management during the COVID-19 Pandemic Emergency: A Literature Review and Single-Center Experience

“…Teledermatology can be classified into real-time teledermatology (VTC—live video consultation) and store-and-forward teledermatology (SAF—image transmission by the patient). Both types of teledermatology have facilitated remote dermatological assistance during the pandemic for chronic diseases and the appearance/modification of skin lesions [ 6 ]. The IDS questioned 678 of its members, from 52 different countries, about their activity during the emergency period.…”

“…Smartphone-based teledermoscopy, an extension of teledermatology, has improved in recent years due to the development of mobile applications and devices. Veronese et al tested an inexpensive and easy-to-use smartphone microscope device; overall, they obtained an accuracy of 83.9% for the diagnoses of skin lesions based on images acquired through the device [ 6 ]. Considering these useful tools, teledermoscopy in association with teledermatology can be used to perform the first triage of skin lesions, helping the clinician to select patients who require a face-to-face consultation [ 8 ].…”

Teledermoscopy in the Diagnosis of Melanocytic and Non-Melanocytic Skin Lesions: NurugoTM Derma Smartphone Microscope as a Possible New Tool in Daily Clinical Practice

“…In 2020, we conducted a study to verify the diagnostic reliability of images acquired through an inexpensive smartphone microscope (Nurugo TM ), employing CNNs to classify malignant melanoma (MM), melanocytic nevus (MN), and seborrheic keratosis (SK). The CNN was tested on three different test sets: (i) ISIC images, (ii) images acquired with the Nurugo TM , and (iii) images acquired with a conventional dermatoscope [ 12 ]. The Nurugo TM device showed an accuracy comparable to conventional dermatoscope (up to 80%), which demonstrates a potential role performing the first triage in TDS, selecting the skin lesions that require a face-to-face consultation with dermatologists [ 12 ].…”

“…The CNN was tested on three different test sets: (i) ISIC images, (ii) images acquired with the Nurugo TM , and (iii) images acquired with a conventional dermatoscope [ 12 ]. The Nurugo TM device showed an accuracy comparable to conventional dermatoscope (up to 80%), which demonstrates a potential role performing the first triage in TDS, selecting the skin lesions that require a face-to-face consultation with dermatologists [ 12 ].…”

Editorial: The Emerging Role of Artificial Intelligence in Dermatology

“…ML models are now being used to classify dermatology clinical images in the electronic health records to optimize access to these images for research purposes ( 51 ). Furthermore, recent studies have demonstrated that dermoscopy improves the diagnostic accuracy of teledermatology ( 52 ); thus, smartphone microscope applications employing CNN are now increasingly supplementing teledermatology consults ( 53 ). Furthermore, because several dermatoses are usually initially seen by primary care providers (PCP), an AI-based tool was developed to interpret images and their associated medical histories, which improved the diagnoses of dermatoses by PCPs in a teledermatology setting ( 54 ).…”