A robust statistical estimation (RoSE) algorithm jointly recovers the 3D location and intensity of single molecules accurately and precisely

Hesam Mazidi; Arye Nehorai; Matthew D. Lew

doi:10.1117/12.2289994

20 February 2018 A robust statistical estimation (RoSE) algorithm jointly recovers the 3D location and intensity of single molecules accurately and precisely

Hesam Mazidi, Arye Nehorai, Matthew D. Lew

Author Affiliations +

Proceedings Volume 10500, Single Molecule Spectroscopy and Superresolution Imaging XI; 105000E (2018) https://doi.org/10.1117/12.2289994
Event: SPIE BiOS, 2018, San Francisco, California, United States

Abstract

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.

Conference Presentation

Citation Download Citation

Hesam Mazidi, Arye Nehorai, and Matthew D. Lew "A robust statistical estimation (RoSE) algorithm jointly recovers the 3D location and intensity of single molecules accurately and precisely", Proc. SPIE 10500, Single Molecule Spectroscopy and Superresolution Imaging XI, 105000E (20 February 2018); https://doi.org/10.1117/12.2289994

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available