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Image Processing - Segmentation Variational Models Osher-Sethian Level-Set Framework + topologically flexible Osher-Sethian Level-Set Framework + topologically.

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Presentation on theme: "Image Processing - Segmentation Variational Models Osher-Sethian Level-Set Framework + topologically flexible Osher-Sethian Level-Set Framework + topologically."— Presentation transcript:

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3 Image Processing - Segmentation Variational Models Osher-Sethian Level-Set Framework + topologically flexible Osher-Sethian Level-Set Framework + topologically flexible Chan-Vese Regional Segmentation + can handle noise + low contrast Chan-Vese Regional Segmentation + can handle noise + low contrast Active Contours Michael Unser B-Splines as Filters + scalability + easy implementation Signal Processing Olivier Bernard: Variational B-Spline Level Set IEEE Transactions On Image Processing, June 2009 Olivier Bernard: Variational B-Spline Level Set IEEE Transactions On Image Processing, June 2009

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9 Image (size) The scale (step size) of the discrete B-Spline function 1248 Time(s) Number of iterations Time(s) Number of iterations. Time(s) Number of iterations Time(s) Number of iterations Leaf (128×128) 0.24000070.22500370.24084780.2105877 Gradient (128×128) 0.360040120.265840100.271019100.2508747 Spiral (128×128) 0.647694240.520128160.304954110.2018917 Stems (128×128) 0.436916150.273539100.25297790.29739511 Brain MRI (128×128) 0.24731480.20042370.16722760.1800826 Echo Image (387×387) 4.001256153.128002112.20984781.9428367

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