Lens-free on-chip digital holographic microscope (LFOCDHM) is crucial for biomedical applications like cell cycle assays, drug development, digital pathology, and high-throughput biological screening. The unit magnification configuration results in a field-of-view (FOV) containing over a hundred times more cells than a conventional 10× microscope objective, making segmentation labor-intensive and time-consuming due to complex and variable cell morphology. Although many deep learning-based cell segmentation methods exist, convolutional neural networks (CNNs) have a limited localized receptive field and are unsuitable for large FOV imaging from LFOCDHM. We propose Swin Transformer U-Net (STU-Net), a high-throughput live cell analysis method. It uses a shift window to compute self-attention and extract features at five scales, achieving accurate cell segmentation (accuracy > 0.9743). We validated STU-Net’s robustness and generalizability with HeLa cell slides across the full FOV in vitro. This approach, capable of quantifying cell growth and proliferation from segmentation results, offers a strong foundation for drug development and biological screening.
High-speed imaging of large numbers of biological samples is critical in numerous biomedical applications. Conventional methods can usually only image a single sample, and for a large number of samples, they can only be imaged sequentially. Here, we propose a dual-plane phase retrieval (DPR) method in the lens-free on-chip microscopy system (LFOCM) based on partially coherent light-emitting diode (LED) illumination. Unlike previous methods, we stack two samples in the axial direction and image both layers simultaneously. Using only five coaxial holograms recorded by the sensor, the phase information of the two layers of stacked samples (including a phase resolution target and a HeLa cell sample) illuminated by LEDs, can be accurately recovered in a large field of view of 19.53 mm2 without compromising their resolution. We quantitatively verified the effectiveness and accuracy of the method in simulations and experiments. The proposed method provides a solution for efficient sample handling in lens-free on-chip microscopy.
We report a wavelength-scanning-based lensless on-chip microscope using a color CMOS sensor and a matching modified phase retrieval algorithm for pixel super-resolution. Without physically removing the Bayer color filter array positioned on the sensor chip, we demonstrate quantitative phase imaging with a lateral resolution of 615 nm over a wide field-of-view of 51.88 mm2 by exploiting the green-channel data from a set of low-resolution holograms captured at various wavelengths. The resulting spatial bandwidth product is 274.3 Megapixels, over 20 times higher than a conventional optical microscope.
A lens-free on-chip digital holographic microscope (LFOCDHM) is essential for a variety of biomedical applications such as cell cycle assays, drug development, digital pathology, and high-throughput biological screening. However, due to the unit magnification configuration of the lens-free system, the field-of-view (FOV) contains over a hundred times more cells than a conventional 10× microscope objective. Consequently, the segmentation process becomes labor-intensive and time-consuming due to the complex and variable morphology of cells within the large FOV. To address this issue, numerous deep learning-based cell segmentation methods have been proposed. Nevertheless, convolutional neural networks, limited by their localized receptive field, are unsuitable for segmenting and processing large FOV imaging results from LFOCDHM. Therefore, we propose a high-throughput live cell analysis processing method called Swin Transformer U-Net (STU-Net). Based on the reconstructed phase results, a shift window is utilized to compute the self-attention to extract its features at five scales, which can compute the normalized inner distance and pixel-level classification and achieve high-throughput accurate cell segmentation (accuracy >0.9743). We validated the robustness and generalizability of our STU-Net by the accurate segmentation of data from HeLa cell slides across the full FOV and live C166 cells in vitro. Given its capability for quantifying cell growth and proliferation based on the multi-cell parameters generated from segmentation results, the proposed approach is expected to provide a strong foundation for subsequent drug development and biological screening.
The lensless in-line holographic microscope offers a compact, low-cost, and wide-field solution for microscopic imaging. Instead of using lenses, lensless microscopy relies on diffraction patterns to reconstruct images of the sample. Therefore, coherent light sources such as lasers are typically used to illuminate the sample for reconstruction images. However, lasers will introduce speckle and multiple reflection interference noise, while also being high in cost. As a result, LED illumination sources have been employed in lensless microscopy systems. However, the temporal coherence of LEDs affects the imaging resolution, which results in poor quality of the reconstructed images. In this paper, we propose an iterative twin image removal method based on a single diffraction pattern based on a lensless on-chip microscopy with a partially coherent illumination source. This method combines the wavelength demultiplexing method with positive absorption constraint and phase flipping. It can not only reduce the temporal coherence limitation of broadband light sources but also improve the convergence speed during iteration and provide better support estimation for complexshaped samples, thus improving the quality of reconstructed images. We provide numerical simulations and optical experiments to illustrate the effectiveness of our method. This work helps extend the application of lensless in-line holographic microscopy based on partially coherent light sources in biomedical detection, offering a more convenient and cost-effective option for microscopic imaging.
We propose a single-frame lensfree phase retrieval(SFLFPR) method based on coherence-limited light-emitting diode (LED) illumination. Combining multi-wavelength scanning iteration for broad-spectrum illumination with phase support constraint, SFLFPR corrects resolution loss caused by the temporal coherence of LED, obtaining quantitative phase imaging results. Using only one hologram, our method can retrieve the high signal-to noise(SNR) phase of the sample and achieve a half-width resolution of 977 nm across a large field-of-view (FOV) of 19.53 mm2 , surpassing 1.41 times the resolution achieved by the conventional single-frame method. We confirmed the effectiveness of this method in quantitative phase imaging (QPI) by measuring various label-free samples including polystyrene microspheres, phase resolution target (PRT) and HeLa cell slices. Considering its fast real-time single-frame imaging capability, our method has a wide range of biological and medical applications.
We report a novel wide-field lens-free 3D microscopy, which is based on Fourier ptychography diffraction tomography (FPDT) technique. This method uses only one illumination angle to obtain a large enough number of diffractograms by scanning a wide range of wavelengths, applying an iterative method to fill the 3D spectrum, and finally recovering the refractive index (RI) distribution of the sample. And the effectiveness of the method in the 3D RI distribution reconstruction of a tilted phase target is experimentally verified.
In traditional lensless in-line holographic microscopy, phase recovery based on multi-defocus distance is a common pixel-super-resolution technique. This method usually requires accurate displacement as a predictive condition, and the introduction of a precision mechanical displacement platform can bring about accurate displacement, but makes a simple lensless system complicated and expensive. In this paper, the samples are illuminated by a nearly coherent illumination system, and holograms at different heights are captured by the sensor driven by a low-cost servo motor without feedback system. Inaccurate displacement interval results in poor phase recovery. We propose a multi-height phase recovery algorithm based on z-axis correction to recover the phase information of the sample, which can improve the result by 1.58 times compared with that before correction. The reconstruction USAF target demonstrates a half-pitch lateral resolution of 775 nm across a large field-ofview of ∼29.84 mm2 , surpassing 2.15 times that of the theoretical Nyquist–Shannon sampling resolution limit imposed by the pixel size of the imaging sensor (1.67 μm).
We report a multi-wavelength multiplexed setup and associated super-resolution reconstruction method in lensless microscopy, which can generate high-resolution reconstructions from undersampled raw measurements captured at multiple wavelengths. The reconstruction result of the Benchmark Quantitative Phase Microscopy Target (QPTTM) demonstrates the resolution enhancement quantitatively, which achieves a half-pitch lateral resolution of 691 nm across a large field of view (~29.85 mm2), surpassing 2.41 times of the theoretical NyquistShannon sampling resolution limit imposed by the pixel-size of the sensor (1.67 µm). Compared with other superresolution methods such as lateral or axial shift-based device and illumination source rotation design, wavelength multiplexed avoids the need for shifting/rotating mechanical components. This multi-wavelength multiplexed super-resolution method would benet the research and development of a more stable lensless microscopy system.
In this paper, we present a multi-wavelength multiplexed setup and associated super-resolution reconstruction method in lensfree microscopy that generates high-resolution reconstructions from undersampled raw measurements captured at multiple wavelengths. The reconstruction result of the standard 1951 USAF achieves a half-pitch lateral resolution of 775 nm, corresponding to a numerical aperture of 1.0, across a large field of view (∼ 29.85 mm2). Compared with other super-resolution methods such as lateral or axial shift-based device and illumination source rotation design, wavelength multiplexed avoids the need for shifting/rotating mechanical components. This multi-wavelength multiplexed super-resolution method would benefit the research and development of a more stable lensfree microscopy system.
We present a wavelength-scanning-based lensfree microscopy that generates high-resolution reconstructions from undersampled raw measurements captured at multiple wavelengths.The reconstruction result of the standard 1951 USAF achieves a half-pitch lateral resolution of 775 nm, corresponding to a numerical aperture of ∼ 1.0, across a large field of view (∼ 29.85 mm2). Compared with other super-resolution methods such as lateral or axial shift-based device and illumination source rotation design, wavelength scanning avoids the need for shifting/rotating mechanical components. This wavelength-scanning super-resolution method would benefit the research and development of more stable lensfree microscopy system.
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