arXiv subjects

Piotr Arcab

Publications and source records attributed to Piotr Arcab.

13 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

YOSO: single-frame Gerchberg-Saxton phase retrieval with AI-based data augmentation for in-line holography

We present YOSO (You Only Shot Once), a single-frame phase retrieval framework for digital in-line holographic microscopy (DIHM) in which supervised deep learning is used to numerically generate an additional hologram corresponding to different defocus distance, creating a so-called multi-height dataset, which is then conventionally processed with a well-established Gerchberg-Saxton (GS) algorithm. YOSO is trained on computer-generated data derived from natural images, enabling strong generalization. The selected multi-scale ResNet architecture enables rapid training in under two hours on a mid-range workstation, which is done only once, enabling efficient inference thereafter. We further show that YOSO network can process inputs of varying spatial dimensions, allowing training on small inputs and direct inference on full-sized holograms while bypassing patch-and-stitch procedure. A further advantage of YOSO is its physics-consistent hologram padding, which replaces conventional zero or edge-value padding with a physically grounded approach compatible with the GS framework. The YOSO framework is tested on various systems (lens-based and lensless DIHM) and diverse samples: a resolution test target, adherent and suspended biological cells, and a mouse brain slice. The results show that YOSO is compatible with 3D objects and correctly recovers defocused object wave features, enabling holographic postprocessing such as numerical refocusing. The results of this work are available publicly as software for end-to-end implementation.

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↗

arXiv2025

High Space-bandwidth Product Label-free Examination of iPSC-derived Brain Organoids via Fourier Ptychographic Microscopy

Fourier ptychographic microscopy (FPM) is a promising quantitative phase imaging technique that enables high-resolution, label-free imaging over a large field-of-view. Here, we present the first application of FPM for the quantitative analysis of human brain organoid slices, providing a powerful, cost-effective, and label-free enhancement to the current gold-standard fluorescence microscopy. Brain organoids, prepared as thin (5 micrometer) slices, were imaged with a custom-built FPM system consisting of a standard light microscope (4x, 0.2 NA objective) and a 7x7 LED array. This configuration achieved a synthetic numerical aperture of 0.54 and a spatial resolution of approximately 488 nm across an area of 2.077 x 3.65 mm. Fluorescence microscopy was used in parallel for neurons, astrocytes, and nuclei labeling, providing rich fluorescence imaging. Moreover, we designed an automated method to merge classical resolution fluorescence images to visualize the whole brain organoid and align it with the numerically increased space-bandwidth product FPM image. The provided alignment method enables rich phase-fluorescence correlative imaging. Based on the segmentation performed on the stitched fluorescence images, we devised a quantitative phase analysis revealing a higher mean optical thickness of the nuclei versus astrocytes and neurons. Notably, nuclei located in neurogenic regions consistently exhibited significantly higher phase values (optical path difference) compared to nuclei elsewhere, suggesting cell-type-specific biophysical signatures. The label-free, quantitative, and high-throughput capabilities of the FPM approach demonstrated here make it a powerful and accessible tool for future structural and functional studies of whole-section brain organoid development and disease modeling studies.

physics.med-ph↗

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

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↗

arXiv2025

Fourier ptychographic microscopy aided with transport of intensity equation for robust full phase spectrum reconstruction

Fourier ptychographic microscopy (FPM) is a pivotal computational imaging technique that achieves phase and amplitude reconstruction with high resolution and wide field of view, using low numerical aperture objectives and LED array illumination. Despite its unique strengths, FPM remains fundamentally limited in retrieving low spatial frequency phase information due to the absence of phase encoding in all brightfield illumination angles. To overcome this, we present a novel hybrid approach that combines FPM with the transport of intensity equation (TIE), enabling accurate, full-spectrum phase retrieval without compromising system simplicity. Our method extends standard FPM acquisitions with a single additional on-axis defocused image, from which low-frequency phase components are reconstructed via TIE method, employing large defocus distance to suppress low-frequency artifacts and enhance robustness to intensity noise. To additionally compensate for defocus-induced magnification variations caused by spherical wavefront illumination, we employ an affine transform-based correction scheme upon image registration. Notably, by restoring the missing low-frequency content, our hybrid method appears capable of recovering phase values beyond the conventional 0-2{\pi} range - an area where conventional FPM techniques often struggle when dealing with optically thick samples. We validated our method using a quantitative phase test target for benchmarking accuracy and biological cheek cells, mouse neurons, and mouse brain tissue slice samples to demonstrate applicability for in vitro bioimaging. Experimental results confirm substantial improvements in phase reconstruction fidelity across spatial frequencies, establishing this hybrid FPM+TIE framework as a practical and high-performance solution for quantitative phase imaging in biomedical and optical metrology applications.

physics.optics↗

arXiv2024

Hybrid iterating-averaging low photon budget Gabor holographic microscopy

One of the primary challenges in live cell culture observation is achieving high-contrast imaging with minimal impact on sample behavior. Quantitative phase imaging (QPI) techniques address this by providing label-free, high-contrast images of transparent samples. Measurement system influence may be further reduced by imaging samples under low illumination intensity (low photon budget - LPB), thereby minimizing photostimulation, phototoxicity, and photodamage, and enabling high-speed imaging. LPB imaging is challenging in QPI due to significant camera shot noise and quantification noise. Digital in-line holographic microscopy (DIHM), working with or without lenses, is a QPI technique known for its robustness to quantification noise. However, reducing simultaneously the camera shot noise and the inherent in-line holographic twin image disturbances remain a critical, yet unaddressed, challenge. This study introduces an innovative iterative Gabor averaging (IGA) algorithm designed specifically for filling this important scientific gap in multi-frame DIHM under LPB conditions. We evaluated the performance of the IGA on simulated data showing that it outperformed traditional algorithms in terms of reconstruction accuracy under high noise conditions. Those results were corroborated by experimental validation involving high-speed imaging of dynamic sperm cells and a phase test target under significantly reduced illumination power. Additionally, the IGA algorithm proved successful in reconstructing optically thin samples, which typically produce low signal-to-noise ratio holograms even under high photon budget conditions. These advancements facilitate photostimulation-free and high-speed imaging of dynamic biological samples and enhance the capability to image samples with extremely low optical thickness, potentially transforming various applications in biomedical and environmental imaging.

physics.optics↗

arXiv2024

Quantitative phase imaging verification in large field-of-view lensless holographic microscopy via two-photon 3D printing

Large field-of-view (FOV) microscopic imaging with high lateral resolution (1-2 microns for high space-bandwidth product) plays a pivotal role in biomedicine and biophotonics, especially within the label-free regime, e.g., for whole slide tissue quantitative analysis and live cell culture imaging. In this context, lensless digital holographic microscopy (LDHM) holds substantial promise. However, one intriguing challenge has been the fidelity of computational quantitative phase imaging (QPI) with LDHM in large FOV. While photonic phantoms, 3D printed by two-photon polymerization (TPP), have facilitated calibration and verification in small FOV lens-based QPI systems, an equivalent evaluation for lensless techniques remains elusive, compounded by issues such as twin-image and beam distortions, particularly towards the detector edges. To tackle this problem, we propose an application of TPP over large area to examine phase consistency in LDHM. In our research, we crafted widefield calibration phase test targets, fabricated them with galvo and piezo scanning, and scrutinized them under single-shot twin-image corrupted conditions and multi-frame iterative twin-image minimization scenarios. By displacing the structures toward the edges of the sensing area, we verified LDHM phase imaging errors across the entire field-of-view, showing less than 12 percent of phase value difference between investigated areas. Interestingly, our research revealed that the TPP technique, following LDHM and Linnik interferometry cross-verification, requires novel design considerations for successful large-area precise photonic manufacturing. Our work thus unveils important avenues toward the quantitative benchmarking of large FOV lensless phase imaging, advancing our mechanistic understanding of LDHM techniques and contributing to their further development and optimization of both phase imaging and fabrication.

physics.optics↗

arXiv2023

Single-shot experimental-numerical twin-image removal in lensless digital holographic microscopy

Lensless digital holographic microscopy (LDHM) offers very large field-of-view label-free imaging crucial, e.g., in high-throughput particle tracking and biomedical examination of cells and tissues. Compact layouts promote point-of-case and out-of-laboratory applications. The LDHM, based on the Gabor in-line holographic principle, is inherently spoiled by the twin-image effect, which complicates the quantitative analysis of reconstructed phase and amplitude maps. Popular family of solutions consists of numerical methods, which tend to minimize twin-image upon iterative process based on data redundancy. Additional hologram recordings are needed, and final results heavily depend on the algorithmic parameters, however. In this contribution we present a novel single-shot experimental-numerical twin-image removal technique for LDHM. It leverages two-source off-axis hologram recording deploying simple fiber splitter. Additionally, we introduce a novel phase retrieval numerical algorithm specifically tailored to the acquired holograms, that provides twin-image-free reconstruction without compromising the resolution. We quantitatively and qualitatively verify proposed method employing phase test target and cheek cells biosample. The results demonstrate that the proposed technique enables low-cost, out-of-laboratory LDHM imaging with enhanced precision, achieved through the elimination of twin-image errors. This advancement opens new avenues for more accurate technical and biomedical imaging applications using LDHM, particularly in scenarios where cost-effective and portable imaging solutions are desired.

physics.optics↗

arXiv2023

Physics-driven universal twin-image removal network for digital in-line holographic microscopy

Digital in-line holographic microscopy (DIHM) enables efficient and cost-effective computational quantitative phase imaging with a large field of view, making it valuable for studying cell motility, migration, and bio-microfluidics. However, the quality of DIHM reconstructions is compromised by twin-image noise, posing a significant challenge. Conventional methods for mitigating this noise involve complex hardware setups or time-consuming algorithms with often limited effectiveness. In this work, we propose UTIRnet, a deep learning solution for fast, robust, and universally applicable twin-image suppression, trained exclusively on numerically generated datasets. The availability of open-source UTIRnet codes facilitates its implementation in various DIHM systems without the need for extensive experimental training data. Notably, our network ensures the consistency of reconstruction results with input holograms, imparting a physics-based foundation and enhancing reliability compared to conventional deep learning approaches. Experimental verification was conducted among others on live neural glial cell culture migration sensing, which is crucial for neurodegenerative disease research.

eess.IV↗

arXiv2023

Low-intensity illumination for lensless digital holographic microscopy with minimized sample interaction

Exposure to laser light alters cell culture examination via optical microscopic imaging techniques, also based on label-free coherent digital holography. To mitigate this detrimental feature, researchers tend to use a broader spectrum and lower intensity of illumination, which can decrease the quality of holographic imaging due to lower resolution and higher noise. We study the lensless digital holographic microscopy (LDHM) ability to operate in the low photon budget (LPB) regime to enable imaging of unimpaired live cells with minimized sample interaction. Low-cost off-the-shelf components are used, promoting the usability of such a straightforward approach. We show that recording data in the LPB regime (down to 7 uW of illumination power) does not limit the contrast nor resolution of the hologram phase and amplitude reconstruction compared to the regular illumination. The LPB generates hardware camera shot noise, however, to be effectively minimized via numerical denoising. The ability to obtain high-quality, high-resolution optical complex field reconstruction was confirmed using the USAF 1951 amplitude sample, phase resolution test target, and finally, live glial restricted progenitor cells (as a challenging strongly absorbing and scattering biomedical sample). The proposed approach based on severely limiting the photon budget in lensless holographic microscopy method can open new avenues in high-throughout (optimal resolution, large field-of-view and high signal-to-noise-ratio single-hologram reconstruction) cell culture imaging with minimized sample interaction.

physics.optics↗

arXiv2023

Experimental optimization of lensless digital holographic microscopy with rotating diffuser-based coherent noise reduction

Laser-based lensless digital holographic microscopy (LDHM) is often spoiled by considerable coherent noise factor. We propose a novel LDHM method with significantly limited coherent artifacts, e.g., speckle noise and parasitic interference fringes. It is achieved by incorporating a rotating diffuser, which introduces partial spatial coherence and preserves high temporal coherence of laser light, crucial for credible in-line hologram reconstruction. We present the first implementation of the classical rotating diffuser concept in LDHM, significantly increasing the signal-to-noise ratio while preserving the straightforwardness and compactness of the LDHM imaging device. Prior to the introduction of the rotating diffusor, we performed LDHM experimental hardware optimization employing 4 light sources, 4 cameras, and 3 different optical magnifications (camera-sample distances). It was guided by the quantitative assessment of numerical amplitude/phase reconstruction of test targets, conducted upon standard deviation calculation (noise factor quantification), and resolution evaluation (information throughput quantification). Optimized rotating diffuser LDHM (RD-LDHM) method was successfully corroborated in technical test target imaging and examination of challenging biomedical sample (60um thick mouse brain tissue slice). Physical minimization of coherent noise (up to 50%) was positively verified, while preserving optimal spatial resolution of phase and amplitude imaging. Coherent noise removal, ensured by proposed RD-LDHM method, is especially important in biomedical inference, as speckles can falsely imitate valid biological features. Combining this favorable outcome with large field-of-view imaging can promote the use of reported RD-LDHM technique in high-throughput stain-free biomedical screening.

physics.optics↗