New methods

Current work

In-focus quantitative phase imaging from defocused off-axis holograms: synergistic reconstruction framework

Digital holographic microscopy (DHM) enables the three-dimensional (3D) reconstruction of quantitative phase distributions from a defocused hologram. Traditional computational algorithms follow a sequential approach in which one first reconstructs the complex amplitude distribution and later applies focusing algorithms to provide an in-focus phase map. In this work, we have developed a synergistic computational framework to compensate for the linear tilt introduced in off-axis DHM systems and autofocus the defocused holograms by minimizing a cost function, providing in-focus reconstructed phase images without phase distortions. The proposed computational tool has been validated in defocused holograms of human red blood cells and three-dimensional images of dynamic sperm cells.

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If you want to download the raw codes in MATLAB 2021a and Python 3.7.1, please click here!

More information can be found here!

Citation:

R. Castaneda, C. Trujillo, and A. Doblas, "In-focus quantitative phase imaging from defocused off-axis holograms: synergistic reconstruction framework," Opt. Letters 48(23), 6244-6247 (2023). doi: 10.1364/OL.506400

Semi-heuristic phase compensation in digital holographic microscopy for stable and accurate quantitative phase imaging of moving objects

Digital holographic microscopy (DHM) is a cutting-edge interferometric technique to recover the complex wavefield scattered by microscopic samples from digitally recorded intensity patterns. In off-axis DHM, the challenge is digitally generating the reference wavefront replica to compensate for the tilt between the interfering waves. Current methods to estimate the reference wavefront's parameters rely on brute-force grid searches or heuristics algorithms. Whereas brute-forced searches are time-consuming and impractical for video-rate quantitative phase imaging and analysis, applying heuristics methods in holographic videos is limited since the phase background level occasionally changes between frames. A semi-heuristic phase compensation (SHPC) algorithm is proposed to address these challenges to reconstruct phase images with minimum distortion in the full field-of-view (FOV) from holograms recorded by a telecentric off-axis digital holographic microscope. The method is tested with a USAF test target, smearing red blood cells and alive human sperm. The SHPC method provides accurate phase maps as the reference brute-force method but with a 92-fold reduction in processing time. Furthermore, this method was tested for reconstructing experimental holographic videos of dynamic specimens, obtaining stable phase values and minimal differences in the background between frames. This proposed method provides state-of-the-art phase reconstructions with high accuracy and stability in holographic videos, allowing the successful XYZ tracking of single-moving sperm cells.

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If you want to download the raw codes written in MATLAB , please click here!

Citation:

S. Obando-Vasquez, A. Doblas, and C. Trujillo, “ Semi-heuristic phase compensation in digital holographic microscopy for stable and accurate quantitative phase imaging of moving objects,” Opt. Lasers Eng. 174, 107937 (2024). doi: 10.1016/j/optlaseng.2023.107937

Comprehensive Tool for a Pase Compensation Reconstruction Method in Digital Holographic Microscopy Operating in Non-Telecentric Regime 

Quantitative phase imaging (QPI) via Digital Holographic microscopy (DHM) has been widely applied in material and biological applications. The performance of DHM technologies relies heavily on computational reconstruction methods to provide accurate phase measurements. Among the optical configuration of the imaging system in DHM, imaging systems operating in a non-telecentric regime are the most common ones. Nonetheless, the spherical wavefront introduced by the non-telecentric DHM system must be compensated to provide undistorted phase measurements. The proposed reconstruction approach is based on previous work from Kemper’s group. Here, we have reformulated the problem, reducing the number of required parameters needed for reconstructing phase images to the sensor pixel size and source wavelength. The developed computational algorithm can be divided into six main steps. In the first step, the selection of the +1-diffraction order in the hologram spectrum. The interference angle is obtained from the selected +1 order. Secondly, the curvature of the spherical wavefront distorting the sample’s phase map is estimated by analyzing the size of the selected +1 order in the hologram’s spectrum. The third and fourth steps are the spatial filtering of the +1 order and the compensation of the interference angle. The next step involves the estimation of the center of the spherical wavefront. An optional final optimization step has been included to fine-tune the estimated parameters and provide fully compensated phase images. Because the proper implementation of a framework is critical to achieve successful results, we have explicitly described the steps, including functions and toolboxes, required for reconstructing phase images without distortions. As a result, we have provided open-access codes and a user interface tool with minimum user input to reconstruct holograms recorded in a non-telecentric DHM system

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If you want to download the raw codes written in MATLAB and Python, a MATLAB GUI, manual, and the non-telecentric holograms, please click here!

Examples of how to use the MATLAB GUI is found in our YouTube channel!


Citation:

B. Bogue-Jimenez, C. Trujillo, and A. Doblas, “Comprehensive Tool for a Pase Compensation Reconstruction Method in Digital Holographic Microscopy Operating in Non-Telecentric Regime,” Plos ONE 18(9), e0291103 (2023).

pyDHM: A Python library for applications in digital holographic microscopy

pyDHM is an open-source Python library aimed at Digital Holographic Microscopy (DHM) applications. The pyDHM is a user-friendly library written in the robust programming language of Python that provides a set of numerical processing algorithms for reconstructing amplitude and phase images for a broad range of optical DHM configurations. The pyDHM implements phase-shifting approaches for in-line and slightly off-axis systems and enables phase compensation for telecentric and non-telecentric systems. In addition, pyDHM includes three propagation algorithms for numerical focusing complex amplitude distributions in DHM and digital holography (DH) setups. We have validated the library using numerical and experimental holograms.

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If you want to download the pyDHM, please click here!

Examples of how to install and use it are found in our YouTube channel!


Citation:

R. Castañeda, C. Trujillo, and A. Doblas, "pyDHM: A Python library for applications in digital holographic microscopy," PLoS ONE 17(10): e0275818 (2022) . https://doi.org/10.1371/journal.pone.0275818

Video-Rate Quantitative Phase Imaging Using a Digital Holographic Microscope and a Generative Adversarial Network

The conventional reconstruction method of off-axis digital holographic microscopy (DHM) relies on computational processing that involves spatial filtering of the sample spectrum and tilt compensation between the interfering waves to accurately reconstruct the phase of a biological sample. Additional computational procedures such as numerical focusing may be needed to reconstruct free-of-distortion quantitative phase images based on the optical configuration of the DHM system. Regardless of the implementation, any DHM computational processing leads to long processing times, hampering the use of DHM for video-rate renderings of dynamic biological processes. In this study, we report on a conditional generative adversarial network (cGAN) for robust and fast quantitative phase imaging in DHM. The reconstructed phase images provided by the GAN model present stable background levels, enhancing the visualization of the specimens for different experimental conditions in which the conventional approach often fails. The proposed learning-based method was trained and validated using human red blood cells recorded on an off-axis Mach–Zehnder DHM system. After proper training, the proposed GAN yields a computationally efficient method, reconstructing DHM images seven times faster than conventional computational approaches.

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If you want to download the trained model, please click here!


Citation:

R. Castaneda, C. Trujillo, and A. Doblas, “Video-Rate Quantitative Phase Imaging Using a Digital Holographic Microscope and a Generative Adversarial Network,” Sensors 21(23), 8021 (2021).

Automatic reconstruction method for quantitative phase image with reduced phase perturbations in off-axis digital holographic microscopy

This works presents a reconstruction algorithm to recover the complex object information for an off-axis digital holographic microscope (DHM) operating in the telecentric regimen. We introduce an automatic and fast method to minimize a cost function that finds the best numerical conjugated reference beam to compensate the filtered object information, eliminating any undesired phase perturbation due to the tilt between the reference and object waves. The novelties of the proposed approach, to the best of our knowledge, are a precise estimation of the interference angle between the object and reference waves, reconstructed phase images without phase perturbations, and reduced processing time. The method has been validated using a manufactured phase target and biological samples.

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Speckle noise reduction in digital holography 

Images recorded by coherent imaging systems, including laser-based photography, digital holography (DH), and digital holographic microscopy (DHM), are severely distorted by speckle noise.  We have worked on a single-shot image processing method to reduce the speckle noise, named as hybrid median-mean filter (HM2F). The HM2F is based on the average of conventional median-filtered images with different kernel size. The synergic combination of the median filter and mean approach provides a denoised image with reduced speckle contrast while the spatial resolution is kept up to 97% from the original value. The HM2F method is compared with the conventional median filter approach (CMF), the 3D Block Matching (BM3D) filter, the non-local means (NLM) filter, the 2D windowed Fourier transform filter (WFT2F), and the Wiener filter using different speckle-distorted images to benchmark its performance. Based on the experimental results and the simplicity of the technique, HM2F is proposed as an effective denoising tool for reducing the speckle noise in laser-based photography, DH, and DHM.

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Blind phase-shifting digital holographic microscopy 

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Past research projects

ApoTome-based Structured illumination Microscopy 

The performance of structured illumination microscopy (SIM) is hampered in many biological applications due to the inability to modulate the light when imaging deep into the sample. This is in part because sample-induced aberration reduces the modulation contrast of the structured pattern. In this paper, we present an image restoration approach suitable for processing raw incoherent-grid-projection SIM data with a low fringe contrast. Restoration results from simulated and experimental ApoTome SIM data show results with an improved signal-to-noise ratio (SNR) and optical sectioning compared to the results obtained from existing methods, such as 2D demodulation and 3D SIM deconvolution. Our proposed method provides satisfactory results (quantified by the achieved SNR and normalized mean square error) even when the modulation contrast of the illumination pattern is as low as 7%. 

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Citation:

N. Patwary, A. Doblas, and C. Preza, “Image restoration approach to address reduced modulation contrast in structured illumination microscopy,” Biomed. Opt. Express 9(4), 1630-1647 (2018).