About: Binarization of noisy microscopy images through signal reconstruction using iterative detection network     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
Description
  • We propose a novel binarization method based on a signal reconstruction using an iterative detection network. The algorithm simulates the whole image acquisition process taking into account a point spread function of the imaging system and its noise characteristics. The negative influence of image blur and noise is effectively suppressed by iterative detection network based on the criterion of maximum a posteriori probability. The proposed method was successfully applied to noisy microscopy images. Experiments show that the proposed method due to the noise suppression and deconvolution properties provides for noisy images significantly better results compared to common thresholding techniques. Binarized images obtained by the proposed method can be particularly useful for particle detection and analysis of cell samples.
  • We propose a novel binarization method based on a signal reconstruction using an iterative detection network. The algorithm simulates the whole image acquisition process taking into account a point spread function of the imaging system and its noise characteristics. The negative influence of image blur and noise is effectively suppressed by iterative detection network based on the criterion of maximum a posteriori probability. The proposed method was successfully applied to noisy microscopy images. Experiments show that the proposed method due to the noise suppression and deconvolution properties provides for noisy images significantly better results compared to common thresholding techniques. Binarized images obtained by the proposed method can be particularly useful for particle detection and analysis of cell samples. (en)
Title
  • Binarization of noisy microscopy images through signal reconstruction using iterative detection network
  • Binarization of noisy microscopy images through signal reconstruction using iterative detection network (en)
skos:prefLabel
  • Binarization of noisy microscopy images through signal reconstruction using iterative detection network
  • Binarization of noisy microscopy images through signal reconstruction using iterative detection network (en)
skos:notation
  • RIV/68407700:21230/14:00222807!RIV15-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GAP102/10/1320), P(LD12018), S
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
  • 5277
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/14:00222807
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Binarization; Microscopy Images; Image Processing; Image Reconstruction; Iterative Detection Network (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [C1153731B7F4]
http://linked.open...v/mistoKonaniAkce
  • Paríž
http://linked.open...i/riv/mistoVydani
  • Piscataway
http://linked.open...i/riv/nazevZdroje
  • 2014 IEEE International Conference on Image Processing (ICIP 2014)
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
  • Fliegel, Karel
  • Klíma, Miloš
  • Kekrt, Daniel
  • Lukeš, Tomáš
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • IEEE
https://schema.org/isbn
  • 978-1-4799-5750-7
http://localhost/t...ganizacniJednotka
  • 21230
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 58 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software