Easy-DHPSF open-source software for three-dimensional localization of single molecules with precision beyond the optical diffraction limit
Automated processing of double-helix (DH) microscope images of single molecules (SMs) streamlines the protocol required to obtain super-resolved three-dimensional (3D) reconstructions of ultrastructures in biological samples by single-molecule active control microscopy. Here, we present a "suite of MATLAB subroutines":https://code.google.com/p/easy-dhpsf/, bundled with an easy-to-use "graphical user interface (GUI)":#f0, that facilitates 3D localization of single emitters (e.g. SMs, fluorescent beads, or quantum dots) with precisions of tens of nanometers in multi-frame movies acquired using a wide-field DH epifluorescence microscope. The algorithmic approach is based upon template matching for SM recognition and least-squares fitting for 3D position measurement, both of which are computationally expedient and precise. Overlapping images of SMs are ignored, and the precision of least-squares fitting is not as high as maximum likelihood-based methods. However, once calibrated, the algorithm can fit 15-30 molecules per second on a 3 GHz Intel Core 2 Duo workstation, thereby producing a 3D super-resolution reconstruction of 100,000 molecules over a 20×20×2 μm field of view (processing 128×128 pixels × 20000 frames) in "75 min":#time_taken.
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Posted 25 Feb, 2013
Easy-DHPSF open-source software for three-dimensional localization of single molecules with precision beyond the optical diffraction limit
Posted 25 Feb, 2013
Automated processing of double-helix (DH) microscope images of single molecules (SMs) streamlines the protocol required to obtain super-resolved three-dimensional (3D) reconstructions of ultrastructures in biological samples by single-molecule active control microscopy. Here, we present a "suite of MATLAB subroutines":https://code.google.com/p/easy-dhpsf/, bundled with an easy-to-use "graphical user interface (GUI)":#f0, that facilitates 3D localization of single emitters (e.g. SMs, fluorescent beads, or quantum dots) with precisions of tens of nanometers in multi-frame movies acquired using a wide-field DH epifluorescence microscope. The algorithmic approach is based upon template matching for SM recognition and least-squares fitting for 3D position measurement, both of which are computationally expedient and precise. Overlapping images of SMs are ignored, and the precision of least-squares fitting is not as high as maximum likelihood-based methods. However, once calibrated, the algorithm can fit 15-30 molecules per second on a 3 GHz Intel Core 2 Duo workstation, thereby producing a 3D super-resolution reconstruction of 100,000 molecules over a 20×20×2 μm field of view (processing 128×128 pixels × 20000 frames) in "75 min":#time_taken.
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