In contrast with common naevi, which generally show a homogeneous and regularly distributed pigmentation, brown to black pigment areas with irregular shape or asymmetric distribution are frequently observable in melanomas. Identification of dark areas inside a melanocytic lesion is of great importance for melanoma diagnosis, both during clinical examination and employing programs for automated image analysis. The aim of our study was to compare two different methods for the automated identification and description of dark areas in epiluminescence microscopy images of melanocytic lesions and to evaluate their diagnostic capability. 339 images of melanocytic lesions, referring to 113 melanomas and 226 melanocytic naevi, acquired by means of a polarizedlight videomicroscope (Videocap 200, DS-medica, Italy) with a 20 fold magnification were studied. Two different methods were employed for the identification of dark areas: the first permits the identification of ‘absolute’ dark areas, defined as areas which are darker than the skin. The second identifies the lesion area, the darkest with respect to the overall brightness of the lesion (‘relative’ dark areas). A set of parameters is extracted both for ‘absolute’ and ‘relative’ dark areas, in order to numerically describe the region properties, such as extension, balance, regularity and symmetry of its distribution. Significant differences in dark area distribution between melanomas and naevi were observed employing both methods, permitting a good discrimination of melanocytic lesions (diagnostic accuracy = 74.6% and 71.2% for absolute and relative dark areas, respectively). In conclusion, both methods for automated identification of dark areas are useful for melanoma diagnosis and can be implemented in programs for image analysis.
Comparison between two methods for automated extraction and description of dark areas in dermoscopic images / Pellacani, Giovanni; Grana, Costantino; A., Martella; Seidenari, Stefania. - In: JOURNAL OF THE EUROPEAN ACADEMY OF DERMATOLOGY AND VENEREOLOGY. - ISSN 0926-9959. - STAMPA. - 17 suppl. 3:(2003), pp. 131-131. (Intervento presentato al convegno 11th Congress of the European academy of Dermatology (EADV) tenutosi a Barcellona, Spagna nel Oct 15-18).
Comparison between two methods for automated extraction and description of dark areas in dermoscopic images
PELLACANI, Giovanni;GRANA, Costantino;SEIDENARI, Stefania
2003
Abstract
In contrast with common naevi, which generally show a homogeneous and regularly distributed pigmentation, brown to black pigment areas with irregular shape or asymmetric distribution are frequently observable in melanomas. Identification of dark areas inside a melanocytic lesion is of great importance for melanoma diagnosis, both during clinical examination and employing programs for automated image analysis. The aim of our study was to compare two different methods for the automated identification and description of dark areas in epiluminescence microscopy images of melanocytic lesions and to evaluate their diagnostic capability. 339 images of melanocytic lesions, referring to 113 melanomas and 226 melanocytic naevi, acquired by means of a polarizedlight videomicroscope (Videocap 200, DS-medica, Italy) with a 20 fold magnification were studied. Two different methods were employed for the identification of dark areas: the first permits the identification of ‘absolute’ dark areas, defined as areas which are darker than the skin. The second identifies the lesion area, the darkest with respect to the overall brightness of the lesion (‘relative’ dark areas). A set of parameters is extracted both for ‘absolute’ and ‘relative’ dark areas, in order to numerically describe the region properties, such as extension, balance, regularity and symmetry of its distribution. Significant differences in dark area distribution between melanomas and naevi were observed employing both methods, permitting a good discrimination of melanocytic lesions (diagnostic accuracy = 74.6% and 71.2% for absolute and relative dark areas, respectively). In conclusion, both methods for automated identification of dark areas are useful for melanoma diagnosis and can be implemented in programs for image analysis.Pubblicazioni consigliate
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris