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Pregled bibliografske jedinice broj: 717806

A divide and conquer strategy for the maximum likelihood localization of low intensity objects


Krull, Alexander; Steinborn, André; Ananthanarayanan, Vaishnavi; Ramunno-Johnson, Damien; Petersohn, Uwe; Tolić-Norrelykke, Iva Marija
A divide and conquer strategy for the maximum likelihood localization of low intensity objects // Optics express, 22 (2014), 1; 210-228 doi:10.1364/OE.22.000210 (međunarodna recenzija, članak, znanstveni)


Naslov
A divide and conquer strategy for the maximum likelihood localization of low intensity objects

Autori
Krull, Alexander ; Steinborn, André ; Ananthanarayanan, Vaishnavi ; Ramunno-Johnson, Damien ; Petersohn, Uwe ; Tolić-Norrelykke, Iva Marija

Izvornik
Optics express (1094-4087) 22 (2014), 1; 210-228

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Single-molecule microscopy ; low-density-lipoprotein ; EM algorithm ; tracking ; cell ; accuracy ; minimum ; motion

Sažetak
In cell biology and other fields the automatic accurate localization of sub-resolution objects in images is an important tool. The signal is often corrupted by multiple forms of noise, including excess noise resulting from the amplification by an electron multiplying charge-coupled device (EMCCD). Here we present our novel Nested Maximum Likelihood Algorithm (NMLA), which solves the problem of localizing multiple overlapping emitters in a setting affected by excess noise, by repeatedly solving the task of independent localization for single emitters in an excess noise-free system. NMLA dramatically improves scalability and robustness, when compared to a general purpose optimization technique. Our method was successfully applied for in vivo localization of fluorescent proteins.

Izvorni jezik
Engleski

Znanstvena područja
Fizika, Biologija



POVEZANOST RADA


Autor s matičnim brojem:
Iva Marija Tolić, (260543)

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


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