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In single-molecule super-resolution microscopy, engineered point-spread functions (PSFs) are designed to efficiently encode new molecular properties, such as 3D orientation, into complex spatial features captured by a camera. To fully benefit from their optimality, algorithms must estimate multi-dimensional parameters such as molecular position and orientation in the presence of PSF overlap and model-experiment mismatches. Here, we present a novel joint sparse deconvolution algorithm based on the decomposition of fluorescence images into six basis images that characterize molecular orientation. The proposed algorithm exploits a group-sparsity structure across these basis images and applies a pooling strategy on corresponding spatial features for robust simultaneous estimates of the number, brightness, 2D position, and 3D orientation of fluorescent molecules. We demonstrate this method by imaging DNA transiently labeled with the intercalating dye YOYO-1. Imaging the position and orientation of each molecule reveals orientational order and disorder within DNA with nanoscale spatial precision.
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A robust statistical estimation (RoSE) algorithm jointly recovers the 3D location and intensity of single molecules accurately and precisely
In single-molecule (SM) super-resolution microscopy, the complexity of a biological structure, high molecular density, and a low signal-to-background ratio (SBR) may lead to imaging artifacts without a robust localization algorithm. Moreover, engineered point spread functions (PSFs) for 3D imaging pose difficulties due to their intricate features. We develop a Robust Statistical Estimation algorithm, called RoSE, that enables joint estimation of the 3D location and photon counts of SMs accurately and precisely using various PSFs under conditions of high molecular density and low SBR.
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- Award ID(s):
- 1653777
- PAR ID:
- 10056146
- Date Published:
- Journal Name:
- Single Molecule Spectroscopy and Superresolution Imaging XI
- Volume:
- 10500
- Page Range / eLocation ID:
- 105000E
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1117/12.2289994
