This package is the companion code to our paper, Phase diversity-based wavefront sensing for fluorescence microscopy.
Given an image contaminated with an unknown aberration and additional images contaminated with the same unknown aberration and additional known aberrations, phase diversity can estimate the wavefront associated with the unknown aberration. This package contains MATLAB code for 2 implementations of Phase Diversity and their dependency functions.
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script_calibration.m- Used for Phase Diversity-based calibration of a deformable mirror. Takes defocus images stacks from a series of voltages applied to each deformable mirror (DM) actuator, estimates wavefronts and computes influence functions. Outputs command matrix (mirror voltages required to issue a desired wavefront). -
processPhaseDiversityImages.m- function designed for on-line (or off-line) calls to estimate wavefronts from an image stack of diversity aberrations applied with a DM. Returns object and wavefront estimate, which can be used to apply optical correction with the DM.
- Requirements
- Installation
- Datasets
- Usage
- References
- License
The code in this package requires MATLAB 23.2 (2023b) with the following toolboxes:
- Image Processing Toolbox
- Statistics and Machine Learning Toolbox
- Curve Fitting Toolbox
- Parallel Computing Toolbox
The MATLAB function dftregistration.m is also required [1], but included in the folder PhaseDiversity/MATLAB code/redist.
A GPU is required to use the flagGPU option.
This code has been tested and verified on Intel Core i7, Intel Xeon, and AMD Ryzen Threadripper CPUs, and Nvidia GeForce and RTX series GPUs.
To use this code, clone the repository or download and unzip it into a suitable location. Add the folder PhaseDiversity and its subfolders to the MATLAB path.
To use the test datasets, download from figshare and unzip the contents so that datasets is a subfolder of the folder PhaseDiversity.
3 full sets of DM calibration data are provided in the data subfolder Datasets/DM Calibration. This folder contains a subfolder for each dataset (e.g.: PD_Cal_1). Each dataset was acquired on a different field of view. Each calibration folder contains a series of subfolders in the form A_n, where n is the number corresponding to each DM actuator. The actuator subfolder then contains an image stack for each of two voltages in the form A_Poke_N.tif where N is the voltage value.
The command matrix can be output using script_calibration.m and pointing to the DM Calibration folder located in PhaseDiversity/Datasets. Figure outputs and MAT data of wavefront estimates, influence functions, and intermediate results of the algorithm can be output by changing the SaveScriptFigures, SaveFunctionFigures and SaveMAT to true. Note that the runtime will slow considerably when figure saving is enabled.
The calibration data was acquired under the following system:
pixelSize= 0.104 (Image Pixel Size in µm)lambda= 0.532 (Central Emission Wavelength in µm)NA= 1.2 (Numerical Aperture)numz= 5 (Number of slices in defocus image stack corresponding to the raw image + number of diversity images)zstepsize= 1 (Space between defocus slices in µm)
Two example sets of AO data are provided in the folder PhaseDiversity/Datasets/AO: an example with multiple beads featuring a scaled test aberration, and a U2OS cell sample with a randomly generated test aberration. Each dataset's folder contains a series of subfolders and two files: GT.tif and CoeffsIn.txt
GT.tif - Ground Truth image before test aberration is applied. For reference only, not used in computation.
CoeffsIn.txt - Table of Zernike Coefficients. Columns correspond to Zernike modes 1-20 (ANSI notation). Rows 2-5 correspond to the known Zernike coefficients for diversity phases. Row 1 is the Zernike coefficients corresponding to the test aberration that are present in all stack images before correction.
Each subfolder is labeled Iteration n where iteration refers to the cycle number/number of wavefront measurements and n corresponds to correction n-1. For example, the subfolder Iteration 1 corresponds to the uncorrected aberrated image and Iteration 2 corresponds to the first correction. In each iteration subfolder is a single file: Stack.tif, which is an image stack corresponding to the raw image and four diversity phases. The first slice in each image stack corresponds to the raw image. In Iteration 1, this slice corresponds to the aberrated image and in Iterations 2...N the first slice corresponds to correction n-1.
Each data set has an associated wrapper function, runPD_TestBeadData and runPD_TestCellData, respectively, which are used to replicate the original on-line calls from LabVIEW. To use, simply call the function with the desired cycle number as input. The function will locate the data folder if PhaseDiversity is found in the MATLAB path and call processPhaseDiversityImages using the original set of input parameters. This function will output the estimated Zernike coefficients, wavefront, and object estimate. It will also return the time to estimate the wavefront, and the difference between the measured wavefront and the expected wavefront for the test aberration.
The input number for the wrapper function is the desired correction cycle equal to n-1 corrections. For example, a value of 1 corresponds to the uncorrected aberrated wavefront and 2 corresponds to the first correction. 10 is the maximum cycle number for the bead test data and 8 is the maximum cycle number for the cell data.
[1] Manuel Guizar-Sicairos, Samuel T. Thurman, and James R. Fienup, "Efficient subpixel image registration algorithms," Opt. Lett. 33, 156-158 (2008).
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