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26 \emph{International Journal of Computer Vision}, vol.~1, no.~4, pp. 321--331,
30 O.~Ruch and P.~R{\'e}fr{\'e}gier, ``Minimal-complexity segmentation with a
31 polygonal snake adapted to different optical noise models,'' \emph{Optics
32 Letters}, vol.~26, no.~13, july 2001.
35 C.~Xu and J.~L. Prince, ``Snakes, shapes, and gradient vector flow,''
36 \emph{IEEE Transactions on Image Processing}, vol.~7, no.~3, pp. 359--369,
39 \bibitem{ChesnaudRB99}
40 C.~Chesnaud, P.~R{\'e}fr{\'e}gier, and V.~Boulet, ``Statistical region
41 snake-based segmentation adapted to different physical noise models,''
42 \emph{IEEE Trans. Pattern Anal. Mach. Intell.}, vol.~21, no.~11, pp.
46 M.~Allain, N.~Bertaux, and F.~Galland, ``Nonparametric level-set segmentation
47 based on the minimization of the stochastic complexity,'' in \emph{ACIVS},
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52 E.~{Dipl.-Inf. Kienel} and G.~{Prof. Dr. Brunnett}, ``Gpu-accelerated contour
53 extraction on large images using snakes,'' 2009. [Online]. Available:
54 \url{http://archiv.tu-chemnitz.de/pub/2009/0035}
55 \BIBentrySTDinterwordspacing
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61 \emph{NVIDIA Fermi Tuning Guide}, NVIDIA Corporation, 7 2010.
64 \emph{NVIDIA Fermi Compatibility Guide}, NVIDIA Corporation, 7 2010.
67 M.~Harris, S.~Sengupta, and J.~D. Owens, \emph{Gpu gems 3}, 1st~ed.\hskip 1em
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