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rdf:type
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Description
| - We present a new algorithm to analyse information content in images acquired using automated fluorescence microscopy. The algorithm belongs to the group of autofocusing methods, but differs from its predecessors in that it can handle thick specimens and operate also in confocal mode. It measures the information content in images using a %22content function%22, which is essentially the same concept as a focus function. Unlike previously presented algorithms, this algorithm tries to find all significant axial positions in cases where the content function applied to real data is not unimodal, which is often the case. This requirement precludes using algorithms that rely on unimodality. Moreover, choosing a content function requires careful consideration, because some functions suppress local maxima. First, we test 19 content functions and evaluate their ability to show local maxima clearly. The results show that only six content functions succeed.
- We present a new algorithm to analyse information content in images acquired using automated fluorescence microscopy. The algorithm belongs to the group of autofocusing methods, but differs from its predecessors in that it can handle thick specimens and operate also in confocal mode. It measures the information content in images using a %22content function%22, which is essentially the same concept as a focus function. Unlike previously presented algorithms, this algorithm tries to find all significant axial positions in cases where the content function applied to real data is not unimodal, which is often the case. This requirement precludes using algorithms that rely on unimodality. Moreover, choosing a content function requires careful consideration, because some functions suppress local maxima. First, we test 19 content functions and evaluate their ability to show local maxima clearly. The results show that only six content functions succeed. (en)
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Title
| - Information Content Analysis in Automated Microscopy Imaging using an Adaptive Autofocus Algorithm for Multimodal Functions
- Information Content Analysis in Automated Microscopy Imaging using an Adaptive Autofocus Algorithm for Multimodal Functions (en)
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skos:prefLabel
| - Information Content Analysis in Automated Microscopy Imaging using an Adaptive Autofocus Algorithm for Multimodal Functions
- Information Content Analysis in Automated Microscopy Imaging using an Adaptive Autofocus Algorithm for Multimodal Functions (en)
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skos:notation
| - RIV/00216224:14330/09:00035554!RIV10-MSM-14330___
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
| - P(2B06052), P(LC535), Z(MSM0021622419)
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http://linked.open...iv/cisloPeriodika
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/00216224:14330/09:00035554
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - automated microscopy; information content analysis; autofocusing; normalized variance (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...odStatuVydavatele
| - GB - Spojené království Velké Británie a Severního Irska
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http://linked.open...ontrolniKodProRIV
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http://linked.open...i/riv/nazevZdroje
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...vavai/riv/projekt
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http://linked.open...UplatneniVysledku
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http://linked.open...v/svazekPeriodika
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http://linked.open...iv/tvurceVysledku
| - Kozubek, Michal
- Brázdilová, Silvie Luisa
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http://linked.open...n/vavai/riv/zamer
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issn
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number of pages
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http://localhost/t...ganizacniJednotka
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