title: Segmentation of Skin Tumors in High-Frequency 3-D Ultrasound Images.
abstract: High-frequency 3-D ultrasound imaging is an informative tool for diagnosis, surgery planning and skin lesion examination. The purpose of this article was to describe a semi-automated segmentation tool providing easy access to the extent, shape and volume of a lesion. We propose an adaptive log-likelihood level-set segmentation procedure using non-parametric estimates of the intensity distribution. The algorithm has a single parameter to control the smoothness of the contour, and we describe how a fixed value yields satisfactory segmentation results with an average Dice coefficient of D = 0.76. The algorithm is implemented on a grid, which increases the speed by a factor of 100 compared with a standard pixelwise segmentation. We compare the method with parametric methods making the hypothesis of Rayleigh or Nakagami distributed signals, and illustrate that our method has greater robustness with similar computational speed. Benchmarks are made on realistic synthetic ultrasound images and a data set of nine clinical 3-D images acquired with a 50-MHz imaging system. The proposed algorithm is suitable for use in a clinical context as a post-processing tool.
authors.affiliation: CREATIS Laboratory, INSA Lyon, France. Electronic address: bruno.sciolla@creatis.insa-lyon.fr.
authors.forename: Bruno
authors.initials: B
authors.lastname: Sciolla
authors.affiliation: Melanoma Skin Cancer Clinic, Hamilton Hill, Western Australia, Australia.
authors.forename: Lester
authors.initials: L
authors.lastname: Cowell
authors.affiliation: Atys Medical, Soucieu-en-Jarrest, France.
authors.forename: Thibaut
authors.initials: T
authors.lastname: Dambry
authors.affiliation: Atys Medical, Soucieu-en-Jarrest, France.
authors.forename: Benoît
authors.initials: B
authors.lastname: Guibert
authors.affiliation: CREATIS Laboratory, INSA Lyon, France.
authors.forename: Philippe
authors.initials: P
authors.lastname: Delachartre
mesh_terms: D000465:Algorithms; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012867:Skin / Q000000981:diagnostic imaging; D012878:Skin Neoplasms / Q000000981:diagnostic imaging*; D014463:Ultrasonography / Q000379:methods*
keywords: Adaptive method; Grid; High-frequency imaging; Level set; Non-parametric method; Segmentation; Three-dimensional imaging; Tumor segmentation