0461983 20240103212525.520160826235959.9 84978902233 000386604000021 10.1007/978-3-319-41501-7_21 8 s. P cav_un_epca*0462001978-3-319-41500-00302-9743183-190ChamSpringer2016 segmentation level set method active contours phase contrast microscopy cav_un_auth*0332672 Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Bílková Zuzana UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0293859 Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Soukup Jindřich UTIA-B CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0021094 Kučera V. CZ http://library.utia.cas.cz/separaty/2016/ZOI/bilkova-0461983.pdf cav_un_auth*0292734 GA13-29225S GA ČR cav_un_auth*0309798 914813/2013 GA UK CZ cav_un_auth*0332704 2016-260332 SVV CZ We present a new method for segmentation of phase-contrast microscopic images of cells. The algorithm is based on the variational for-mulation of the level set method, i.e. minimizing of a functional, which describes the level set function. The functional is minimized by a gradi-ent ow described by an evolutionary partial dierential equation. The most signicant new ideas are initialization using thresholding and the introduction of a new term based on local variance that speeds up con-vergence and achieves more accurate results. The proposed algorithm is applied on real data and compared with another algorithm. cav_un_auth*0332703 International Conference Image Analysis and Recognition 2016 20160713 20160715 Póvoa de Varzim PT JD 2017 3 PR RVO:67985556 http://hdl.handle.net/11104/0261538 S n.a. Proceedings Paper Computer Science Artificial Intelligence|Computer Science Theory Methods|Imaging Science Photographic Technology 0.325 Q2 Q2 2016 84978902233 SCOPUS 000386604000021 WOS cav_un_epca*0462001 Image Analysis and Recognition : 13th International Conference, ICIAR 2016 978-3-319-41500-0 0302-9743 183 190 Cham Springer 2016 Lecture Notes in Computer Science 9730