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EnglishThe 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].
| Titolo: | Automatic Extraction of Dermatological Parameters from Nevi Using an Inexpensive Smartphone Microscope: A Proof of Concept | |
| Autori: | ||
| Data di pubblicazione: | 2019 | |
| Serie: | ||
| Abstract: | The evolution of smartphone technology has made their use more common in dermatological applicati...ons. 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. | |
| ISBN: | 978-1-5386-1311-5 | |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| Automatic_Extraction_of_Dermatological_Parameters_from_Nevi_Using_an_Inexpensive_Smartphone_Microscope_A_Proof_of_Concept.pdf | 2a Post-print versione editoriale / Version of Record | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia | |
| EMBC19_1204_FI.pdf | 2. Post-print / Author's Accepted Manuscript | PUBBLICO - Tutti i diritti riservati | Visibile a tuttiVisualizza/Apri |
http://hdl.handle.net/11583/2931563
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