Synthesis of arbitrary interference patterns using a single galvanometric mirror

<h3>Version 1</h3> <p>CAD model</p> <p>Speed accessment images (images of fluorescent beads using 100 X microscope) and postprocessing code in MATLAB</p> <p>Laser interference images and postprocessing code in MATLAB</p> <ul> <li>Two beam and hexagonal pattern images were repeated multiple times</li> <li>Three beam images were taken at different axial positions</li> </ul> <p>2D SIM data with 100 nm fluorescent beads (two examples,&nbsp;<em>2D 1ms 980Hz 400mW.tiff </em>and <em>2D 1ms 980Hz 400mW.tiff</em>, not TIRF) and reconstruction code in MATLAB (<em>SIM_reconstrcution_2D.m</em>)</p> <ul> <li>Use <em>set_default_figure_parameters.m&nbsp;</em>to set the default figure unit to cm</li> <li>The camera jittered during the measurements. The images were shifted to cancel the jitter using <a href="https://uk.mathworks.com/matlabcentral/fileexchange/18401-efficient-subpixel-image-registration-by-cross-correlation">Efficient subpixel image registration by cross-correlation - File Exchange - MATLAB Central</a>. For comparison, two images are reconstructed, with and without cancelling the jitter&nbsp;</li> <li>Each set of measurement contain multiple cycles of 11 frames, of which the 4th and 8th frames are discarded</li> <li>Parameters are estimated using function <em>estimate_sim_parameters_KG.m</em></li> <li>Images are reconstructed using function <em>reconstruct_sim2_KG.m</em></li> <li>For reference, the images are averaged and have the PSF deconvolved using <em>deconv_Wiener_KG.m</em></li> </ul> <p>3D SIM data (<em>3D cell cropped.tiff),&nbsp;</em>widefield reference data (<em>WF cropped.tiff</em>) and reconstruction code in MATLAB (<em>SIM3D_cells.m</em>)</p> <ul> <li>Use <em>set_default_figure_parameters.m&nbsp;</em>to set the default figure unit to cm</li> <li>Parameters are estimated from a subset of the image (which has higher SNR) using function <em>estimate_sim_parameters_3D_KG.m</em></li> <li>Images are reconstructed using function <em>reconstruct_sim_3D_KG.m</em></li> <li>For reference, a widefield 3D image was captured by only illuminating the sample with one laser beam. The image is further processed using <em>WF3D_cells.m</em> and function <em>deconv_3D.m&nbsp;</em>to deconvolve the OTF</li> <li>The theorectial OTF is calculated using code from <a href="https://github.com/jdmanton/debye_diffraction_code">https://github.com/jdmanton/debye_diffraction_code</a> which is included in the package</li> </ul> <h3>Version 2</h3> <p>2D TIRF SIM data with 100 nm fluorescent beads (same as Version 3) and reconstruction code in MATLAB. I forgot to upload background noise image. Please use Version 3 to avoid error in running the code</p> <h3>Version 3&nbsp;</h3> <p>2D TIRF SIM data with 100 nm fluorescent beads (same as Version 2) and reconstruction code including FRC in MATLAB (<em>main.m</em>)</p> <ul> <li>Use <em>set_default_figure_parameters.m&nbsp;</em>to set the default figure unit to cm</li> <li>Raw data include two sets of measurements (<em>TIRF beads.tiff and TIRF beads 2.tiff</em>) and background noise image (<em>bg 1ms.tiff</em>)</li> <li>Each set of measurement (e.g. <em>TIRF beads.tiff</em>) contain two cycles of 11 frames, of which the 4th and 8th frames are discarded in each cycle</li> <li>Parameters are estimated using function <em>estimate_sim_parameters_KG.m</em></li> <li>Images are reconstructed using function <em>reconstruct_sim2D_KG.m</em></li> <li>For reference, the images are averaged and have the PSF deconvolved using <em>deconv_Wiener_KG.m</em></li> </ul> <p>3D SIM data (same as Version 1) and reconstruction code for FRC in MATLAB (<em>main.m</em>)</p> <ul> <li>Use <em>set_default_figure_parameters.m&nbsp;</em>to set the default figure unit to cm</li> <li>Two subsets of the image were taken for FRC, one with even z steps and one with odd z steps</li> <li>Parameters are estimated using function <em>estimate_sim_parameters_KG.m</em></li> <li>Images are reconstructed using function <em>reconstruct_sim2D_KG.m</em></li> <li>The two subsets are reconstructed independently (double z step size) and the centre z position of each image are used to calculate FRC</li> <li>Only subsets of the image are processed. Refer to Version 1 for larger range in z.</li> </ul> <p>Stability accessment images (two beam laser interference images taken over periods of time) and postprocessing code in MATLAB</p> <p>2D SIM (not TIRF) data with 200 nm fluorescent beads measured over the full FOV and reconstruction code in MATLAB</p> <ul> <li>Processed in almost the same way as 2D TIRF SIM</li> <li>Parameters were estimated using the centre of the FOV</li> <li>Sections with ~10 um horizontal distances are plotted to show change of quality across the FOV</li> </ul> <p>PSF data measured using 200 nm fluorescent beads and postprocessing code in MATLAB</p> <ul> <li>Individual bead images are picked and fit with theoretical PSF function to obtain resolution</li> <li>Beads with ~10 um horizontal distances are plotted to show change of quality across the FOV</li> </ul>