. . "Huben\u00FD, Jan" . "Springer-Verlag" . . . "4"^^ . "3rd International Symposium on Visual Computing" . "RIV/00216224:14330/07:00022769!RIV10-MSM-14330___" . "Berlin, Heidelberg" . "Svoboda, David" . . . "11"^^ . . . "Lake Tahoe, Nevada/California" . "978-3-540-76855-5" . "14330" . "4"^^ . . . . "2007-11-26+01:00"^^ . . "Image segmentation, one of the fundamental task of image processing, can be accurately solved using the level set framework. However, the computational time demands of the level set methods make them practically useless, especially for segmentation of large threedimensional images. Many approximations have been introduced in recent years to speed up the computation of the level set methods. Although these algorithms provide favourable results, most of them were not properly tested against ground truth images. In this paper we present a comparison of three methods: the Sparse-Field method [1], Deng and Tsui's algorithm [2] and Nilsson and Heyden's algorithm [3]. Our main motivation was to compare these methods on 3D image data acquired using fluorescence microscope, but we suppose that presented results are also valid and applicable to other biomedical images like CT scans, MRI or ultrasound images." . "A Comparison of Fast Level Set-Like Algorithms for Image Segmentation in Fluorescence Microscopy"@en . . . . "Image segmentation, one of the fundamental task of image processing, can be accurately solved using the level set framework. However, the computational time demands of the level set methods make them practically useless, especially for segmentation of large threedimensional images. Many approximations have been introduced in recent years to speed up the computation of the level set methods. Although these algorithms provide favourable results, most of them were not properly tested against ground truth images. In this paper we present a comparison of three methods: the Sparse-Field method [1], Deng and Tsui's algorithm [2] and Nilsson and Heyden's algorithm [3]. Our main motivation was to compare these methods on 3D image data acquired using fluorescence microscope, but we suppose that presented results are also valid and applicable to other biomedical images like CT scans, MRI or ultrasound images."@en . . . "P(2B06052), P(LC535), Z(MSM0021622419)" . . "A Comparison of Fast Level Set-Like Algorithms for Image Segmentation in Fluorescence Microscopy"@en . "407822" . . "A Comparison of Fast Level Set-Like Algorithms for Image Segmentation in Fluorescence Microscopy" . . "RIV/00216224:14330/07:00022769" . "image segmentation; level set method; active contours"@en . . "A Comparison of Fast Level Set-Like Algorithms for Image Segmentation in Fluorescence Microscopy" . . "Kozubek, Michal" . "000251785200056" . "Ma\u0161ka, Martin" . "[2AE7553E9EDA]" .