TY - JOUR
T1 - A divide and conquer strategy for the maximum likelihood localization of low intensity objects
AU - Krull, Alexander
AU - Steinborn, André
AU - Ananthanarayanan, Vaishnavi
AU - Ramunno-Johnson, Damien
AU - Petersohn, Uwe
AU - Tolić-Nørrelykke, Iva M
PY - 2014/1/13
Y1 - 2014/1/13
N2 - 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.
AB - 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.
U2 - 10.1364/OE.22.000210
DO - 10.1364/OE.22.000210
M3 - Article
SN - 1094-4087
VL - 22
SP - 210
EP - 228
JO - Optics Express
JF - Optics Express
IS - 1
ER -