title: Skin lesion segmentation using an improved snake model.
abstract: Accurate identification of lesion borders is an important task in the analysis of dermoscopy images since the extraction of skin lesion borders provides important cues for accurate diagnosis. Snakes have been used for segmenting a variety of medical imagery including dermoscopy, however, due to the compromise of internal and external energy forces they can lead to under- or over-segmentation problems. In this paper, we introduce a mean shift based gradient vector flow (GVF) snake algorithm that drives the internal/external energies towards the correct direction. The proposed segmentation method incorporates a mean shift operation within the standard GVF cost function. Experimental results on a large set of diverse dermoscopy images demonstrate that the presented method accurately determines skin lesion borders in dermoscopy images.
authors.affiliation: The Institute of Electronics, Communications and Information Technology (ECIT), Queen's University Belfast, United Kingdom.
authors.forename: Huiyu
authors.initials: H
authors.lastname: Zhou
authors.forename: Gerald
authors.initials: G
authors.lastname: Schaefer
authors.forename: M
authors.initials: M
authors.lastname: Celebi
authors.forename: Hitoshi
authors.initials: H
authors.lastname: Iyatomi
authors.forename: Kerri-Ann
authors.initials: KA
authors.lastname: Norton
authors.forename: Tangwei
authors.initials: T
authors.lastname: Liu
authors.forename: Faquan
authors.initials: F
authors.lastname: Lin
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D046169:Dermoscopy / Q000379:methods*; D004195:Disease Models, Animal; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007834:Lasers; D015233:Models, Statistical; D015999:Multivariate Analysis; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012867:Skin / Q000473:pathology*; D012911:Snakes