arXiv subjects

Piotr Zdankowski

Publications and source records attributed to Piotr Zdankowski.

9 recordsLinked to original sources

arXiv2026

Hybrid spectral-spatial domain registration for nanometric tracking in digital in-line holographic microscopy

Digital in-line holographic microscopy enables label-free tracking and metrology, but achieving nanometric sub-pixel displacement accuracy over a wide capture range remains challenging. Frequency-domain registration based on the discrete Fourier transform (DFT) is globally stable and tolerant to large shifts, yet it suffers from sub-pixel quantization and interpolation artifacts that limit precision near zero displacement. In contrast, spatial-gradient refinement such as Lucas-Kanade (LK) can reach very high sub-pixel accuracy, but it is strongly initialization-limited and prone to divergence outside a narrow convergence basin. Here we propose a Hybrid Spectral-Spatial Domain (HSSD) framework that resolves this trade-off by combining the global robustness of a DFT-based coarse estimator with LK refinement of the residual motion. The DFT stage provides reliable initialization and substantially extends the capture range, while the LK stage suppresses the precision floor by reducing interpolation and quantization errors characteristic of standalone frequency-domain methods. We validate HSSD using numerical simulations and experiments in a transmission in-line holographic imaging system, achieving nanoprecision displacement measurement and stable tracking across a wide range of displacements and defocusing conditions. This hybrid strategy enables reliable nanometric localization in regimes where standalone DFT or LK methods either fail to converge or saturate in accuracy.

physics.optics↗

arXiv2026

Near-infrared lensless holographic microscopy on a visible sensor enables label-free high-throughput imaging in strong scattering

Lensless digital holographic microscopy (LDHM) relies on interference between an unscattered reference wave and a weakly scattered object wave - an assumption that rapidly fails in turbid samples under multiple scattering. To overcome this limitation, we present near-infrared LDHM (NIR-LDHM), a in-line holographic platform that operates up to the silicon cutoff (~1100 nm) using a conventional board-level CMOS sensor designed for visible (VIS) imaging. Using tissue-mimicking milk scattering layers and calibrated resolution targets, we quantify reconstruction performance versus wavelength, scattering strength, and sample-sensor distance. NIR-LDHM maintains resolvable features through scattering layers up to ~1.4 mm, whereas visible regime fails to resolve features below ~350 um. Importantly, despite a detector quantum efficiency of only 0.19% at 1100 nm, robust reconstructions are obtained under low-photon-budget conditions. We further identify advantageous mechanism by which increasing the sample-sensor distance from ~3 to 12 mm improves lateral resolution by twofold under strong scattering. Finally, we demonstrate wide-field, label-free amplitude-phase imaging of uncleared mouse tissues, resolving internal structure in brain and liver slices up to ~250 um and ~60 um, respectively. By extending lensless complex-field microscopy into strongly scattering regimes with minimal hardware changes, this work has relevance to computational imaging through complex media and biophotonics.

physics.optics↗

arXiv2026

The mixture of glycerin with tartrazine: a solution to reversibly increase tissue transparency for in vitro quantitative phase imaging

Thick tissue sections strongly scatter and absorb light, which limits transmission-based label-free examination via quantitative phase imaging (QPI) modalities. Here we introduce a simple, room-temperature optical clearing medium - glycerol and tartrazine solution (GTS; 60 percent glycerol, 10 percent tartrazine) - that increases the transparency of 50-80 micron murine liver and kidney slices while preserving tissue morphology and enabling rapid, label-free quantitative phase imaging. Using Fourier ptychographic microscopy (FPM) and lensless digital holographic microscopy with pixel super-resolution (LDHM-PSR), we demonstrate markedly improved high-throughput visualization of microstructural features after GTS immersion compared with phosphate-buffered saline (PBS). The improvement is confirmed quantitatively by a significant increase in the one-pixel-lag autocorrelation of phase-gradient values, indicating reduced scattering-driven phase artifacts and enhanced structural continuity in reconstructed phase maps. We further show that GTS is stable for months at room temperature, provides instant yet durable clearing that improves over time, and can be removed by brief PBS washing, enabling downstream multimodal analyses on the same specimen. Finally, we benchmark GTS against the state-of-the-art clearing agent Ce3D, highlighting GTS as a low-cost, safe, operationally straightforward alternative with strong potential for routine, high-throughput QPI-based histopathology workflows.

physics.optics↗

arXiv2026

Lateral shearing optical diffraction tomography of brain organoid with reduced spatial coherence

Optical diffraction tomography (ODT) is a powerful technique for quantitative, label-free reconstruction of the three-dimensional refractive index (RI) distribution of biological samples. While ODT is well established for imaging thin, weakly scattering samples, it encounters significant challenges when applied to heterogeneous, strongly scattering thick samples such as tissues and organoids. In this work, a novel common-path interferometric approach to ODT is presented, specifically designed for the RI reconstruction of heterogeneous and highly scattering samples at high temporal stability. The proposed technique, termed lateral shearing (LS)-ODT, incorporates partial lateral shearing off-axis interferometry to suppress the effects of multiple scattering, similar to the mechanism in differential interference contrast (DIC) microscopy, which is widely used for imaging thick specimens. Additionally, the LS-ODT system uses dynamic speckle illumination to enhance both spatial phase and RI sensitivity compared to laser-based ODT systems. The effectiveness of this method is demonstrated through experiments on a cell phantom. Its robustness and accuracy are further validated across a wide range of samples, including mouse kidney tissue sections and brain organoids derived from human induced pluripotent stem cells (iPSCs), in both thin and thick sections. Furthermore, correlative fluorescence and RI tomography of the organoids highlights the potential of LS-ODT to enhance and support a broad spectrum of biomedical studies, particularly in the field of histology.

physics.optics↗

arXiv2025

Low-dose Chemically Specific Bioimaging via Deep-UV Lensless Holographic Microscopy on a Standard Camera

Deep-ultraviolet (DUV) microscopy can provide label-free biochemical contrast by exploiting the intrinsic absorption of nucleic acids, proteins and lipids, offering chemically specific morphological information that complements structural optical thickness contrast from phase-sensitive imaging. However, existing DUV microscopes typically rely on specialized optics and DUV-sensitive cameras, which restrict field of view, increase system complexity and cost, and often require high illumination doses that risk photodamage. Here, we report a low-dose deep-UV lensless holographic microscopy platform that uses standard board-level CMOS sensors designed for visible light, eliminating all imaging optics and dedicated DUV detectors. Our system achieves large field-of-view (up to 116 mm2) DUV imaging with low illumination and label-free phase and chemically specific amplitude contrast. A specialized defocus/wavelength diverse pixel super-resolution reconstruction with total-variation regularization and robust autofocusing halves the effective sensor pixel pitch and yields down to 870 nm lateral resolution. We demonstrate chemically specific, label-free bioimaging on challenging specimens, including Saccharomyces cerevisiae, extracellular vesicles and unstained mouse liver tissue. In liver sections, imaging at {\lambda} = 330 nm reveals lipid- and retinoid-rich accumulations that co-localize with Oil Red O staining, enabling label-free identification of hepatic stellate (Ito) cells. This combination of low-dose operation, chemically specific contrast and standard CMOS hardware establishes DUV lensless holographic microscopy as a practical and scalable route to high-content submicron-resolution whole-slide preparation-free bioimaging without exogenous labels.

physics.optics↗

arXiv2025

Bayesian inference for precise and uncertainty-quantified single-shot widefield interferometric geometrical nanometrology

Advanced geometrical nanometrology is critical for process control in semiconductor manufacturing, supporting applications in, e.g., photonic integrated circuits, nanoelectronics, and emerging quantum and optoelectronic technologies. Widefield interferometric approach provide a cost-effective, non-destructive solution for characterizing semiconductor optical waveguides, which are fundamental to nanophotonic devices. This work presents a Bayesian inference framework, implemented using Dynamic Nested Sampling, for estimating geometric parameters - such as width and height - of a semiconductor optical waveguide from a single widefield interferogram. The proposed framework reduces the need of leveraging near field scanning microscopy methods for measurements. The notable advantage is that Bayesian statistics not only provide the estimated parameter values but also quantify the uncertainty of the inference results and the fitness of the used model. The proposed full-field, single-shot interferometric approach, supported by Bayesian-based data analysis, achieves high accuracy and sensitivity - down to successful measurement of 8 nm rib waveguide - while remaining resilient to noise. Thus, the demonstrated methodology provides a cost-effective, robust, and scalable tool for semiconductor fabrication monitoring and process verification, as confirmed by both numerical simulations and experimental validation on optical waveguides. This method contributes to high-precision nanometrology by integrating advanced statistical modeling and inference techniques.

physics.optics↗

arXiv2025

Gigavoxel-Scale Multiple-Scattering-Aware Lensless Holotomography

Holotomography (HT) has revolutionized quantitative label-free 3D imaging, yet conventional lens-based implementations are fundamentally constrained in field-of-view (FOV) and imaging depth, limiting their utility for critical high-throughput applications in material and life sciences. Lensless HT (LHT) offers a promising alternative for large-volume examination, however existing approaches fail to accurately reconstruct highly scattering samples over extended depths, which remains a critical challenge in optical imaging field. Here, we introduce a gigavoxel-scale, multiple-scattering-aware LHT with a large FOV (surpassing 0.6 cm2), millimeter-scale axial range and pixel level (~2.4 micron) resolution. Our approach leverages a multi-wavelength, oblique-illumination hologram reconstruction and a robust, automatic illumination angle calibration, which are necessary for precise large-volume 3D holographic reconstruction. Moreover, we propose optimization-driven multi-slice tomographic framework to accurately capture multiple-scattering effects outperforming first order Born/Rytov-based inversions. To rigorously validate our method, we reconstruct bespoke multi-layer two-photon polymerized test structure over a 1.7 mm imaging depth and 25 mm2 FOV, yielding an unprecedented 3D space-bandwidth product exceeding a gigavoxel level. Furthermore, we demonstrate for the first time on-chip label-free imaging of entire 500-micron-thick tissue slice of optically-cleared mouse brain. With the proposed method, we aim to unlock powerful new capabilities for large-scale, quantitative, label-free 3D imaging across biomedicine, neuroscience, material sciences and beyond.

physics.optics↗

arXiv2024

Gradient Optical Diffraction Tomography

Optical diffraction tomography (ODT) enables non-invasive information-rich 3D refractive index (RI) reconstruction of unimpaired transparent biological and technical samples, crucial in biomedical research, optical metrology, materials sciences, and other fields. ODT bypasses the inherent limitations of 2D integrated quantitative phase imaging methods. To increase the signal-to-noise ratio easy-to-implement common-path shearing interferometry setups are successfully combined with low spatiotemporal coherence of illumination. The need for self-interference generated holograms, with small shear values, critically impedes the analysis of dense and thick samples, e.g., cell cultures, tissue sections, and embryos/organoids. Phase gradient imaging techniques, deployed as a popular solution in the small shear regime, up to now were constrained to 2D integrated quasi-quantitative phase imaging and z-scanning for depth resolution. To fill this significant scientific gap, we propose a novel gradient optical diffraction tomography (GODT) method. The GODT uses coherence-tailored illumination-scanning sequence of phase gradient measurements to tomographically reconstruct, for the first time to the best of our knowledge, a derivative of the 3D RI distribution (in the shear direction) with clearly visible 3D sample structure and high sensitivity to its spatial variations. We present a mathematically rigorous theory based on the first-order Rytov approximation behind the new method, validate it using simulations deploying numerical Shepp-Logan target and corroborate experimentally via successful tomographic imaging of the calibrated nano-printed cell phantom and efficient examination of neural cells. This novel imaging modality opens new possibilities in biomedical quantitative phase imaging, advancing the field and putting forward a first of a kind contrast domain: 3D RI gradient.

physics.optics↗

arXiv2022

Tailoring 2D Fast Iterative Filtering algorithm for low-contrast optical fringe pattern preprocessing

Retrieving object phase from the optical fringe pattern is a critical task in quantitative phase imaging and often requires appropriate image preprocessing (background and noise minimization), especially when retrieving phase from the single-shot fringe pattern image. In this article, for the first time, we propose to adapt the 2D Fast Iterative Filtering (FIF) method for fringe pattern decomposition and develop a novel version of FIF called the 2D fringe pattern Fast Iterative Filtering (fpFIF2), that is tailored for fringe pattern preprocessing. We show the positive influence of fpFIF2 onto fringe pattern filtering comparing to the previous 2D FIF implementation regarding processing speed, quality, and usage comfortability. We also compare the fpFIF2 with other state-of-the-art fringe pattern filtering methods in terms of aiding the Hilbert spiral transform method in phase retrieval. Employing numerical simulations and experimental fringe analysis, we prove that fpFIF2 outperforms reference methods, especially in terms of low-fringe-contrast phase reconstruction quality and decomposition time.

physics.optics↗