Title :
Skin lesion segmentation using an improved snake model
Author :
Zhou, Huiyu ; Schaefer, Gerald ; Celebi, M. Emre ; Iyatomi, Hitoshi ; Norton, Kerri-Ann ; Liu, Tangwei ; Lin, Faquan
Author_Institution :
Inst. of Electron., Queen´´s Univ. Belfast, Belfast, UK
fDate :
Aug. 31 2010-Sept. 4 2010
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.
Keywords :
cancer; edge detection; image segmentation; medical image processing; skin; dermoscopy; external energy; gradient vector flow cost function; internal energy; mean shift operation; segmentation; skin lesion borders; snake model; Euclidean distance; Force; Image edge detection; Image segmentation; Lesions; Level set; Skin; Algorithms; Animals; Artificial Intelligence; Dermoscopy; Disease Models, Animal; Humans; Image Interpretation, Computer-Assisted; Lasers; Models, Statistical; Multivariate Analysis; Pattern Recognition, Automated; Reproducibility of Results; Skin; Snakes;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location :
Buenos Aires
Print_ISBN :
978-1-4244-4123-5
DOI :
10.1109/IEMBS.2010.5627556