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Computer description of colours in dermoscopic melanocytic lesion images reproducing clinical assessment
Author(s) -
Seidenari S.,
Pellacani G.,
Grana C.
Publication year - 2003
Publication title -
british journal of dermatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.304
H-Index - 179
eISSN - 1365-2133
pISSN - 0007-0963
DOI - 10.1046/j.1365-2133.2003.05496.x
Subject(s) - lesion , palette (painting) , dermatoscopy , medicine , melanoma , artificial intelligence , nevus , dermatology , computer science , pattern recognition (psychology) , pathology , cancer research , operating system
Summary Background The assessment of colours is essential for the diagnosis of malignant melanoma (MM), both for pattern analysis on dermoscopic images, and when employing semiquantitative methods. Objectives To develop a computer program for colour assessment in MM images mimicking the human perception of lesion colours, and to compare the automatic colour evaluation with one performed by human observers. Methods A colour palette comprising six colour groups (black, dark brown, light brown, blue–grey, red and white) was created by selecting single colour components inside melanocytic lesion images acquired by means of a digital videomicroscope, and was implemented in the image analysis program. Subsequently, colours were assessed by the computer program on 331 melanocytic lesion images composing our image database, and the results were compared with the evaluation of lesion colours performed by the clinician. Results The black, white and blue–grey colours were more frequently found in MMs than in naevi, both by the clinicians and by the computer. In MM images we observed 4·27 ± 1·14 colours (mean ± SD) per lesion, as opposed to 3·22 ± 0·68 in naevi. The correlation between clinical and computer evaluation of the colours was very good, with a value of 0·781 for overall assessment. Conclusions This innovative method for automatic colour evaluation, reproducing clinical assessment of melanocytic lesion colours, may provide numerical parameters to be employed for computer‐aided diagnosis of MM.