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Updated: Jun 18, 2026

SCAnED - An Open-source Skin Segmentation Macro for Semi-automated Cell and Nuclei Detection in Epidermal and Dermal Skin Compartments
Published on: August 8, 2025
Variability in human and automatic segmentation of melanocytic lesions
A Silletti1, E Peserico, A Mantovan
1Department of Information Engineering, University of Padova, Italy. melanoma@dei.unipd.it
Abstract:
In a double blind evaluation of 60 digital dermatoscopic images by 4 "junior", 4 "senior" and 4 "expert" dermatologists (dermatoscopy training respectively less than 1 year, between 1 and 5 years, and more than 5 years), a significant inter-operator variability was observed in melanocytic lesion border identification (with a disagreement of the order of 10 - 20% of the area of the lesions). Expert dermatologists showed greater agreement among themselves than with senior and junior dermatologists, and a slight tendency towards "tighter" segmentations. The human inter-operator variability was then used to evaluate the segmentation accuracy of 4 algorithms, representative of the 3 fundamental state-of-the-art automated segmentation techniques and of a fourth, novel, technique. Our evaluation methodology addresses a number of crucial difficulties encountered in previous studies and may be of independent interest. 3 of the 4 algorithms showed considerably less agreement with expert dermatologists than even senior and junior dermatologists did (with a disagreement of the order of 30% of the area of the lesions); the remaining algorithm, however, showed agreement with expert dermatologists comparable to that of other expert dermatologists.