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  • In fluorescence microscopy, the proper evaluation of image segmentation algorithms is still an open problem. In the field of cell segmentation, such evaluation can be seen as a study of the given algorithm how well it can discover individual cells as a function of the number of them in an image (size of cell population), their mutual positions (density of cell clusters), and the level of noise. Principally, there are two approaches to the evaluation. One approach requires real input images and an expert that verifies the segmentation results. This is, however, expert dependent and, namely when handling 3D data, very tedious. The second approach uses synthetic images with ground truth data to which the segmentation result is compared objectively. In this paper, we propose a new method for generating synthetic 3D images showing naturally distributed cell populations attached to microscope slide. Cell count and clustering probability are user parameters of the method.
  • In fluorescence microscopy, the proper evaluation of image segmentation algorithms is still an open problem. In the field of cell segmentation, such evaluation can be seen as a study of the given algorithm how well it can discover individual cells as a function of the number of them in an image (size of cell population), their mutual positions (density of cell clusters), and the level of noise. Principally, there are two approaches to the evaluation. One approach requires real input images and an expert that verifies the segmentation results. This is, however, expert dependent and, namely when handling 3D data, very tedious. The second approach uses synthetic images with ground truth data to which the segmentation result is compared objectively. In this paper, we propose a new method for generating synthetic 3D images showing naturally distributed cell populations attached to microscope slide. Cell count and clustering probability are user parameters of the method. (en)
Title
  • Towards a Realistic Distribution of Cells in Synthetically Generated 3D Cell Populations
  • Towards a Realistic Distribution of Cells in Synthetically Generated 3D Cell Populations (en)
skos:prefLabel
  • Towards a Realistic Distribution of Cells in Synthetically Generated 3D Cell Populations
  • Towards a Realistic Distribution of Cells in Synthetically Generated 3D Cell Populations (en)
skos:notation
  • RIV/00216224:14330/13:00066208!RIV14-GA0-14330___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GBP302/12/G157)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 111342
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14330/13:00066208
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • cell populations; simulation; cross-correlation (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [7CC061552DBE]
http://linked.open...v/mistoKonaniAkce
  • Naples, Italy
http://linked.open...i/riv/mistoVydani
  • Berlin, Heidelberg
http://linked.open...i/riv/nazevZdroje
  • 17th International Conference on Image Analysys and Processing - ICIAP 2013
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Svoboda, David
  • Ulman, Vladimír
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000329811200044
http://linked.open.../riv/zahajeniAkce
issn
  • 0302-9743
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/978-3-642-41184-7_44
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 9783642411830
http://localhost/t...ganizacniJednotka
  • 14330
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