Next Article in Journal
Oxidative and Nitrosative Stress in the Metastatic Microenvironment
Next Article in Special Issue
Cerebral Metastases from Malignant Melanoma: Current Treatment Strategies, Advances in Novel Therapeutics and Future Directions
Previous Article in Journal
Identification of Insulin-Like Growth Factor-I Receptor (IGF-IR) Gene Promoter-Binding Proteins in Estrogen Receptor (ER)-Positive and ER-Depleted Breast Cancer Cells
Previous Article in Special Issue
Biology of Human Cutaneous Melanoma
Review

Automated Dermoscopy Image Analysis of Pigmented Skin Lesions

1
Department of Biochemistry, Section of Pathology, Second University of Naples, Via L. Armanni 5, 80138 Naples, Italy
2
Futura-onlus, Via Pordenone 2, 00182 Rome, Italy
3
ACS, Advanced Computer Systems, Via della Bufalotta 378, 00139 Rome, Italy
*
Author to whom correspondence should be addressed.
Cancers 2010, 2(2), 262-273; https://doi.org/10.3390/cancers2020262
Received: 23 February 2010 / Revised: 15 March 2010 / Accepted: 25 March 2010 / Published: 26 March 2010
(This article belongs to the Special Issue Current Concepts in the Diagnosis and Treatment of Cutaneous Melanoma)
Dermoscopy (dermatoscopy, epiluminescence microscopy) is a non-invasive diagnostic technique for the in vivo observation of pigmented skin lesions (PSLs), allowing a better visualization of surface and subsurface structures (from the epidermis to the papillary dermis). This diagnostic tool permits the recognition of morphologic structures not visible by the naked eye, thus opening a new dimension in the analysis of the clinical morphologic features of PSLs. In order to reduce the learning-curve of non-expert clinicians and to mitigate problems inherent in the reliability and reproducibility of the diagnostic criteria used in pattern analysis, several indicative methods based on diagnostic algorithms have been introduced in the last few years. Recently, numerous systems designed to provide computer-aided analysis of digital images obtained by dermoscopy have been reported in the literature. The goal of this article is to review these systems, focusing on the most recent approaches based on content-based image retrieval systems (CBIR). View Full-Text
Keywords: melanoma; dermoscopy; digital images; content-based image retrieval (CBIR) melanoma; dermoscopy; digital images; content-based image retrieval (CBIR)
Show Figures

Graphical abstract

MDPI and ACS Style

Baldi, A.; Quartulli, M.; Murace, R.; Dragonetti, E.; Manganaro, M.; Guerra, O.; Bizzi, S. Automated Dermoscopy Image Analysis of Pigmented Skin Lesions. Cancers 2010, 2, 262-273. https://doi.org/10.3390/cancers2020262

AMA Style

Baldi A, Quartulli M, Murace R, Dragonetti E, Manganaro M, Guerra O, Bizzi S. Automated Dermoscopy Image Analysis of Pigmented Skin Lesions. Cancers. 2010; 2(2):262-273. https://doi.org/10.3390/cancers2020262

Chicago/Turabian Style

Baldi, Alfonso, Marco Quartulli, Raffaele Murace, Emanuele Dragonetti, Mario Manganaro, Oscar Guerra, and Stefano Bizzi. 2010. "Automated Dermoscopy Image Analysis of Pigmented Skin Lesions" Cancers 2, no. 2: 262-273. https://doi.org/10.3390/cancers2020262

Find Other Styles

Article Access Map by Country/Region

1
Only visits after 24 November 2015 are recorded.
Back to TopTop