BACKGROUND/ PURPOSE: Automatic lesion segmentation is an important part of computer-based image analysis of pigmented skin lesions. In this research, a watershed algorithm is developed and investigated for adequacy of skin lesion segmentation in dermoscopy images. METHODS: Hair, black border and vignette removal methods are introduced as preprocessing steps. The flooding variant of the watershed segmentation algorithm was implemented with novel features adapted to this domain. An outer bounding box, determined by a difference function derived from horizontal and vertical projection functions, is added to estimate the lesion area, and the lesion area error is reduced by a linear estimation function. As a post-processing step, a second-order B-Spline smoothing method is introduced to smooth the watershed border. RESULTS: Using the average of three sets of dermatologist-drawn borders as the ground truth, an overall error of 15.98% was obtained using the watershed technique. CONCLUSION: The implementation of the flooding variant of the watershed algorithm presented here allows satisfactory automatic segmentation of pigmented skin lesions.
BACKGROUND/ PURPOSE:Automatic lesion segmentation is an important part of computer-based image analysis of pigmented skin lesions. In this research, a watershed algorithm is developed and investigated for adequacy of skin lesion segmentation in dermoscopy images. METHODS: Hair, black border and vignette removal methods are introduced as preprocessing steps. The flooding variant of the watershed segmentation algorithm was implemented with novel features adapted to this domain. An outer bounding box, determined by a difference function derived from horizontal and vertical projection functions, is added to estimate the lesion area, and the lesion area error is reduced by a linear estimation function. As a post-processing step, a second-order B-Spline smoothing method is introduced to smooth the watershed border. RESULTS: Using the average of three sets of dermatologist-drawn borders as the ground truth, an overall error of 15.98% was obtained using the watershed technique. CONCLUSION: The implementation of the flooding variant of the watershed algorithm presented here allows satisfactory automatic segmentation of pigmented skin lesions.
Authors: M Emre Celebi; Y Alp Aslandogan; William V Stoecker; Hitoshi Iyatomi; Hiroshi Oka; Xiaohe Chen Journal: Skin Res Technol Date: 2007-11 Impact factor: 2.365
Authors: Hanzheng Wang; Randy H Moss; Xiaohe Chen; R Joe Stanley; William V Stoecker; M Emre Celebi; Joseph M Malters; James M Grichnik; Ashfaq A Marghoob; Harold S Rabinovitz; Scott W Menzies; Thomas M Szalapski Journal: Comput Med Imaging Graph Date: 2010-10-20 Impact factor: 4.790
Authors: Jomy J Varghese; M Eva Hansen; Azmeer Sharipol; Matthew H Ingalls; Martha A Ormanoski; Shawn D Newlands; Catherine E Ovitt; Danielle S W Benoit Journal: Arch Oral Biol Date: 2018-10-22 Impact factor: 2.633