The evolution of smartphone technology has made their use more common in dermatological applications. Here we studied the feasibility of using an inexpensive smartphone microscope for the extraction of dermatological parameters and compared the results obtained with a portable dermoscope, commonly used in clinical practice. Forty-two skin lesions were imaged with both devices and visually analyzed by an expert dermatologist. The presence of a reticular pattern was observed in 22 dermoscopic images, but only in 10 smartphone images. The proposed paradigm segments the image and extracts texture features which are used to train and validate a neural network to classify the presence of a reticular pattern. Using 5-fold cross-validation, an accuracy of 100% and 95% was obtained with the dermoscopic and smartphone images, respectively. This approach can be useful for general practitioners and as a triage tool for skin lesion analysis.

Automatic Extraction of Dermatological Parameters from Nevi Using an Inexpensive Smartphone Microscope: A Proof of Concept / Meiburger, K. M.; Veronese, F.; Tarantino, V.; Salvi, M.; Fadda, M.; Seoni, S.; Zavattaro, E.; Santi, B. D.; Michielli, N.; Savoia, P.; Molinari, F.. - ELETTRONICO. - 2019:(2019), pp. 399-402. (Intervento presentato al convegno 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 tenutosi a Berlin, Germany nel 23-27 July 2019) [10.1109/EMBC.2019.8856720].

Automatic Extraction of Dermatological Parameters from Nevi Using an Inexpensive Smartphone Microscope: A Proof of Concept

Meiburger K. M.;Salvi M.;Seoni S.;Michielli N.;Molinari F.
2019

Abstract

The evolution of smartphone technology has made their use more common in dermatological applications. Here we studied the feasibility of using an inexpensive smartphone microscope for the extraction of dermatological parameters and compared the results obtained with a portable dermoscope, commonly used in clinical practice. Forty-two skin lesions were imaged with both devices and visually analyzed by an expert dermatologist. The presence of a reticular pattern was observed in 22 dermoscopic images, but only in 10 smartphone images. The proposed paradigm segments the image and extracts texture features which are used to train and validate a neural network to classify the presence of a reticular pattern. Using 5-fold cross-validation, an accuracy of 100% and 95% was obtained with the dermoscopic and smartphone images, respectively. This approach can be useful for general practitioners and as a triage tool for skin lesion analysis.
2019
978-1-5386-1311-5
File in questo prodotto:
File Dimensione Formato  
Automatic_Extraction_of_Dermatological_Parameters_from_Nevi_Using_an_Inexpensive_Smartphone_Microscope_A_Proof_of_Concept.pdf

non disponibili

Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 4.91 MB
Formato Adobe PDF
4.91 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
EMBC19_1204_FI.pdf

accesso aperto

Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: PUBBLICO - Tutti i diritti riservati
Dimensione 4.47 MB
Formato Adobe PDF
4.47 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2931563