Sean Quirin

Optimal 3D single-molecule localization for superresolution microscopy with aberrations and engineered point spread functions

Photo-activation localization microscopy is a far-field superresolution imaging technique based on the localization of single molecules with subdiffraction limit precision. Known under acronyms such as PALM (photo-activated localization microscopy) or STORM (stochastic optical reconstruction microscopy), these techniques achieve superresolution by allowing only a sparse, random set of molecules to emit light at any given time and subsequently localizing each molecule with great precision. Recently, such techniques have been extended to three dimensions, opening up unprecedented possibilities to explore the structure and function of cells. Interestingly, proper engineering of the three-dimensional (3D) point spread function (PSF) through additional optics has been demonstrated to theoretically improve 3D position estimation and ultimately resolution. In this paper, an optimal 3D single-molecule localization estimator is presented in a general framework for noisy, aberrated and/or engineered PSF imaging. To find the position of each molecule, a phase-retrieval enabled maximum-likelihood estimator is implemented. This estimator is shown to be efficient, meaning it reaches the fundamental Cramer–Rao lower bound of x, y, and z localization precision. Experimental application of the phase-retrieval enabled maximum-likelihood estimator using a particular engineered PSF microscope demonstrates unmatched low-photon-count 3D wide-field single-molecule localization performance.

Quantitative multicolor subdiffraction imaging of bacterial protein ultrastructures in three dimensions.

We demonstrate quantitative multicolor three-dimensional (3D) subdiffraction imaging of the structural arrangement of fluorescent protein fusions in living Caulobacter crescentus bacteria. Given single-molecule localization precisions of 20-40 nm, a flexible locally weighted image registration algorithm is critical to accurately combine the super-resolution data with <10 nm error. Surface-relief dielectric phase masks implement a double-helix response at two wavelengths to distinguish two different fluorescent labels and to quantitatively and precisely localize them relative to each other in 3D.

Super-resolution photon-efficient imaging by nanometric double-helix point spread function localization of emitters (SPINDLE)

Super-resolution imaging with photo-activatable or photo-switchable probes is a promising tool in biological applications to reveal previously unresolved intra-cellular details with visible light. This field benefits from developments in the areas of molecular probes, optical systems, and computational post-processing of the data. The joint design of optics and reconstruction processes using double-helix point spread functions (DH-PSF) provides high resolution three-dimensional (3D) imaging over a long depth-of-field. We demonstrate for the first time a method integrating a Fisher information efficient DH-PSF design, a surface relief optical phase mask, and an optimal 3D localization estimator. 3D super-resolution imaging using photo-switchable dyes reveals the 3D microtubule network in mammalian cells with localization precision approaching the information theoretical limit over a depth of 1.2 µm.

Photon efficient double-helix PSF microscopy with application to 3D photo-activation localization imaging

We present a double-helix point spread function (DH-PSF) based three-dimensional (3D) microscope with efficient photon collection using a phase mask fabricated by gray-level lithography. The system using the phase mask more than doubles the efficiency of current liquid crystal spatial light modulator implementations. We demonstrate the phase mask DH-PSF microscope for 3D photo-activation localization microscopy (PM-DH-PALM) over an extended axial range.

Depth estimation and image recovery using broadband, incoherent illumination with engineered point spread functions [Invited].

The use of complementary engineered point spread functions is proposed for the joint tasks of depth estimation and image recovery over an extended depth of field. A digital imaging system with a dynamically adjustable pupil is demonstrated experimentally. The implementation of a broadband, passive camera is demonstrated with a fractional ranging error of 4/10(4) at a working distance of 1 m. Once the depth and brightness information of a scene are obtained, a synthetic camera is defined and images rendered computationally to emphasize particular features such as image focusing at different depths.

Limits of 3D dipole localization and orientation estimation for single-molecule imaging: towards Green’s tensor engineering

The 3D orientation and location of individual molecules is an important marker for the local environment and the state of a molecule. Therefore dipole localization and orientation estimation is important for biological sensing and imaging. Precise dipole localization is also critical for superresolution imaging. We propose and analyze wide field microscope configurations to simultaneously measure these parameters for multiple fixed dipole emitters. Examination of the images of radiating dipoles reveals how information transfer and precise detection can be improved. We use an information theoretic analysis to quantify the performance limits of position and orientation estimation through comparison of the Cramer-Rao lower bounds in a photon limited environment. We show that bi-focal and double-helix polarization-sensitive systems are attractive candidates for simultaneously estimating the 3D dipole location and orientation.

Pattern Matching Estimator for Precise 3-D Particle Localization with Engineered Point Spread Functions

We present a 3-D particle localization estimator that uses phase retrieval to interpolate the calibration images of the point-spread-function and finds the best fit to the measured data. We analyze the application to double-helix microscopy.

Double helix PSF engineering for computational fluorescence microscopy imaging

Point spread function engineering with a double helix (DH) phase mask has been recently used in a joint computationaloptical approach for the determination of depth and intensity information from fluorescence images. In this study, theoretically determined DH-PSFs computed from a model that incorporates different amounts of depth-induced spherical aberration (SA) due to refractive-index mismatch in the three-dimensional imaging layers, are evaluated through a comparison to empirically determined DH-PSFs measured from quantum dots. The theoretically-determined DH-PSFs show a trend that captures the main effects observed in the empirically-determined DH-PSFs. Calibration curves computed from these DH-PSFs show that SA slows down the rate of rotation observed in a DH-PSF which results in: 1) an extended range of rotation; and 2) asymmetric rotation ranges as the focus is moved in opposite directions. Thus, for accurate particle localization different calibration curves need to be known for different amounts of SA. Results also show that the DH-PSF is less sensitive to SA than the conventional PSF. Based on this result, it is expected that fewer depth-variant (DV) DH-PSFs will be required for 3D computational microscopy imaging in the presence of SA compared to the required number of conventional DV PSFs.

Double-Helix PSF Microscopy with a Phase Mask for Efficient Photon Collection

We present the first implementation of double-helix phase masks for 3D microscopy with high photon collection efficiency. The mask is fabricated using gray-level mask-less lithography. The system demonstrates precise 3D tracking of quantum dots.

3-D Imaging Using Helical Point Spread Functions

We engineer three-dimensional point spread functions to collect the information required for depth recovery and imaging. We investigate computational imaging systems using helical point spread functions for 3-D passive imaging and compare with prevailing methods. Article not available.