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We propose a novel single-plane phase retrieval method to realize high-quality sample reconstruction for lensfree on-chip microscopy. In our method, complex wavefield reconstruction is modeled as a quadratic minimization problem, where total variation and joint denoising regularization are designed to keep a balance of artifact removal and resolution enhancement. In experiment, we built a 3D-printed field-portable platform to validate the imaging performance of our method, where resolution chart, dynamic target, transparent cell, polystyrene beads, and stained tissue sections are employed for the imaging test. Compared to state-of-the-art methods, our method eliminates image degradation and obtains a higher imaging resolution. Different from multi-wavelength or multi-height phase retrieval methods, our method only utilizes a single-frame intensity data record to accomplish high-fidelity reconstruction of different samples, which contributes a simple, robust, and data-efficient solution to design a resource-limited lensfree on-chip microscope. We believe that it will become a useful tool for telemedicine and point-of-care application.
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http://dx.doi.org/10.1364/OE.458400 | DOI Listing |
Opt Lett
February 2025
Lens-free on-chip microscopy (LFOCM) is a high-throughput computational imaging technique that enables high-resolution, label-free imaging without requiring complex optical systems. However, LFOCM encounters significant challenges in achieving high-resolution reconstructions due to noise accumulation. We propose a high-fidelity LFOCM method that integrates pixel super-resolution (PSR) with dynamic dual-channel noise separation (DCNS).
View Article and Find Full Text PDFSensors (Basel)
December 2024
Smart Computational Imaging Laboratory (SCILab), School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
Lens-free on-chip microscopy (LFOCM) is a powerful computational imaging technology that combines high-throughput capabilities with cost efficiency. However, in LFOCM, the phase recovered by iterative phase retrieval techniques is generally wrapped into the range of -π to π, necessitating phase unwrapping to recover absolute phase distributions. Moreover, this unwrapping process is prone to errors, particularly in areas with large phase gradients or low spatial sampling, due to the absence of reliable initial guesses.
View Article and Find Full Text PDFLight Sci Appl
September 2024
Smart Computational Imaging (SCI) Laboratory, Nanjing University of Science and Technology, No. 200 Xiaolingwei Street, 210094, Nanjing, Jiangsu, China.
Lens-free on-chip microscopy is a powerful and promising high-throughput computational microscopy technique due to its unique advantage of creating high-resolution images across the full field-of-view (FOV) of the imaging sensor. Nevertheless, most current lens-free microscopy methods have been designed for imaging only two-dimensional thin samples. Lens-free on-chip tomography (LFOCT) with a uniform resolution across the entire FOV and at a subpixel level remains a critical challenge.
View Article and Find Full Text PDFOpt Express
January 2024
Auto-focusing is an essential task for lens-free holographic microscopy, which has developed many methods for high precision or fast refocusing. In this work, we derive the relationship among intensity derivation, the derivative of spectral distribution, as well as the distribution of the object, and propose a new auto-focusing criterion, the Robert critical function with axial difference (RCAD), to enhance the accuracy of distance estimation for lens-free imaging with the ultra-broadband light source. This method consists of three steps: image acquisition and preprocessing, axial-difference calculation, and distance estimation with sharpness analysis.
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