Resolution and Contrast Enhancement for Lensless Digital Holographic Microscopy and Its Application in Biomedicine

Improving the Signal-to-Noise Ratio of Axial Displacement Measurements of Microspheres Based on Compound Digital Holography Microscopy Combined with the Reconstruction Centering Method

In 3D microsphere tracking, unlike in-plane motion that can be measured directly by a microscope, axial displacements are resolved by optical interference or a diffraction model. As a result, the axial results are affected by the environmental noise. The immunity to environmental noise increases with measurement accuracy and the signal-to-noise ratio (SNR). In compound digital holography microscopy (CDHM)-based measurements, precise identification of the tracking marker is critical to ensuring measurement precision. The reconstruction centering method (RCM) was proposed to suppress the drawbacks caused by installation errors and, at the same time, improve the correct identification of the tracking marker. The reconstructed center is considered to be the center of the microsphere, rather than the center of imaging in conventional digital holographic microscopy. This method was verified by simulation of rays tracing through microspheres and axial moving experiments. The axial displacements of silica microspheres with diameters of 5 μm and 10 μm were tested by CDHM in combination with the RCM. As a result, the SNR of the proposed method was improved by around 30%. In addition, the method was successfully applied to axial displacement measurements of overlapped microspheres with a resolution of 2 nm.

Enhancing Light-Sheet Fluorescence Microscopy Illumination Beams through Deep Design Optimization

Light sheet fluorescence microscopy (LSFM) provides the benefit of optical sectioning coupled with rapid acquisition times for imaging of tissue-cleared specimen. This allows for high-resolution 3D imaging of large tissue volumes. Inherently to LSFM, the quality of the imaging heavily relies on the characteristics of the illumination beam, with the notion that the illumination beam only illuminates a thin section that is being imaged. Therefore, substantial efforts are dedicated to identifying slender, non-diffracting beam profiles that can yield uniform and high-contrast images. An ongoing debate concerns the employment of the most optimal illumination beam; Gaussian, Bessel, Airy patterns and/or others. Comparisons among different beam profiles is challenging as their optimization objective is often different. Given that our large imaging datasets (~0.5TB images per sample) is already analyzed using deep learning models, we envisioned a different approach to this problem by hypothesizing that we can tailor the illumination beam to boost the deep learning models performance. We achieve this by integrating the physical LSFM illumination model after passing through a variable phase mask into the training of a cell detection network. Here we report that the joint optimization continuously updates the phase mask, improving the image quality for better cell detection. Our method's efficacy is demonstrated through both simulations and experiments, revealing substantial enhancements in imaging quality compared to traditional Gaussian light sheet. We offer valuable insights for designing microscopy systems through a computational approach that exhibits significant potential for advancing optics design that relies on deep learning models for analysis of imaging datasets.

Multi-Illumination Single-Holographic-Exposure Lensless Fresnel (MISHELF) Microscopy: Principles and Biomedical Applications

Lensless holographic microscopy (LHM) comes out as a promising label-free technique since it supplies high-quality imaging and adaptive magnification in a lens-free, compact and cost-effective way. Compact sizes and reduced prices of LHMs make them a perfect instrument for point-of-care diagnosis and increase their usability in limited-resource laboratories, remote areas, and poor countries. LHM can provide excellent intensity and phase imaging when the twin image is removed. In that sense, multi-illumination single-holographic-exposure lensless Fresnel (MISHELF) microscopy appears as a single-shot and phase-retrieved imaging technique employing multiple illumination/detection channels and a fast-iterative phase-retrieval algorithm. In this contribution, we review MISHELF microscopy through the description of the principles, the analysis of the performance, the presentation of the microscope prototypes and the inclusion of the main biomedical applications reported so far.

Computational Portable Microscopes for Point-of-Care-Test and Tele-Diagnosis

In bio-medical mobile workstations, e.g., the prevention of epidemic viruses/bacteria, outdoor field medical treatment and bio-chemical pollution monitoring, the conventional bench-top microscopic imaging equipment is limited. The comprehensive multi-mode (bright/dark field imaging, fluorescence excitation imaging, polarized light imaging, and differential interference microscopy imaging, etc.) biomedical microscopy imaging systems are generally large in size and expensive. They also require professional operation, which means high labor-cost, money-cost and time-cost. These characteristics prevent them from being applied in bio-medical mobile workstations. The bio-medical mobile workstations need microscopy systems which are inexpensive and able to handle fast, timely and large-scale deployment. The development of lightweight, low-cost and portable microscopic imaging devices can meet these demands. Presently, for the increasing needs of point-of-care-test and tele-diagnosis, high-performance computational portable microscopes are widely developed. Bluetooth modules, WLAN modules and 3G/4G/5G modules generally feature very small sizes and low prices. And industrial imaging lens, microscopy objective lens, and CMOS/CCD photoelectric image sensors are also available in small sizes and at low prices. Here we review and discuss these typical computational, portable and low-cost microscopes by refined specifications and schematics, from the aspect of optics, electronic, algorithms principle and typical bio-medical applications.