A coarse-to-fine approach for segmenting melanocytic skin lesions in standard camera images.
Melanoma is a type of malignant melanocytic skin lesion, and it is among the most life threatening existing cancers if not treated at an early stage. Computer-aided prescreening systems for melanocytic skin lesions is a recent trend to detect malignant melanocytic skin lesions in their early stages, and lesion segmentation is an important initial processing step. A good definition of the lesion area and its border is very important for discriminating between benign and malignant cases. In this paper, we propose to segment melanocytic skin lesions using a sequence of steps. We start by pre-segmenting the skin lesion, creating a new image representation (channel) where the lesion features are more evident. This new channel is thresholded, and the lesion border pre-detection is refined using an active-contours algorithm followed by morphological operations. Our experimental results based on a publicly available dataset suggest that our method potentially can be more accurate than comparable state-of-the-art methods proposed in literature.
Instituto de Informática, Universidade Federal do Rio Grande do Sul. Avenida Bento Gonçalves 9500, Porto Alegre 91501-970, RS, Brazil. Electronic address: pgcavalcanti@inf.ufrgs.br.
Pablo G
PG
Cavalcanti
Jacob
J
Scharcanski
D006801:Humans; D008545:Melanoma / Q000473:pathology*; D010781:Photography; D012878:Skin Neoplasms / Q000473:pathology*
Computer-aided diagnosis; Melanocytic skin lesion; Melanoma; Segmentation; Standard cameras