arXiv subjects

Yoshiaki Yasuno

Publications and source records attributed to Yoshiaki Yasuno.

At least 19 recordsLinked to original sources

arXiv2026

Numerical speckle reduction for optical coherence tomography based on an analytical image formation model

Speckle is an intrinsic granular pattern that limits the effective resolution of optical coherence tomography (OCT). We propose a numerical speckle reduction method using the "real part of a shifted complex conjugate product" (real-SCCP), which is a new image representation designed based on an analytical imaging model of OCT. In the real-SCCP image representation, the speckle can be fully numerically modulated after OCT signal acquisition. By averaging multiple SCCP images with different speckle realizations, the speckle is effectively reduced. Furthermore, this method enables clear visualization of structures in tumor spheroids and zebrafish eyes, and significantly outperforms conventional frame-averaging-based speckle reduction techniques.

physics.optics↗

arXiv2026

High-speed volumetric amplitude-spectrum dynamic optical coherence tomography by neural network with multi-burst scanning

Dynamic optical coherence tomography (DOCT) enables label-free, three-dimensional (3D) assessment of tissue dynamics. However, it suffers from long acquisition times because conventional time-spectrum DOCT requires hundreds of repeated OCT frames per location. Here we present a neural network (NN) framework integrated with a non-uniform-time scanning protocol (multi-burst scan) to accelerate amplitude-spectrum DOCT (AS-DOCT). Combining 3D convolutional and long-short term memory (LSTM) layers with dual inputs (the temporal OCT sequence and its pseudo-amplitude spectrum), the model generates AS-DOCT images from only 16 frames per location. Validated on 29 cancer spheroids, the proposed method resolved distinct functional domain structures with high fidelity (structural similarity index metric (SSIM) > 0.8) and enabled full volumetric AS-DOCT acquisition in 26.2 seconds. This method will enable high-throughput 3D dynamic tissue screening.

physics.optics↗

arXiv2026

Image-based investigation of the zebrafish developmental process using in vivo dynamic and multi-contrast optical coherence tomography

We demonstrate in vivo dynamic optical coherence tomography (DOCT) imaging of zebrafish development from 2 weeks to 12 months post-fertilization, integrated with polarization-sensitive OCT (PS-OCT), OCT angiography (OCTA), and histological validation. Two DOCT algorithms were utilized: logarithmic intensity variance and late OCT correlation decay speed, which characterize the occupancy of dynamic scatterers and their motion speeds, respectively. Our results show that skin stripes exhibit high DOCT signals and it varies among the pigment-cell types. Furthermore, the combination of DOCT and PS-OCT captures the maturation of these stripes. In addition, DOCT and OCTA successfully visualized the developmental progression of blood and lymphatic vessels, as well as spinal tissues.

physics.optics↗

arXiv2026

Neural-network-based high-speed and high-definition full-field dynamic optical coherence tomography

A neural-network (NN)-based method for high-speed, high-definition dynamic optical coherence tomography (DOCT) using full-field swept-source optical coherence microscopy (FF-SS-OCM) is demonstrated. FF-SS-OCM provides high-definition OCT images, but, particularly in DOCT imaging, it results in a significant enlargement of the data size and subsequently long data streaming and processing time, which prevents high-throughput imaging. We address this issue by introducing an NN-based DOCT method that generates high-definition logarithmic intensity variance (LIV) -based DOCT images from only four OCT volumes, whereas the conventional method required 32 volumes. The NN model successfully generates an LIV image that is qualitatively and quantitatively similar to the LIV image computed from 32 volumes. This approach significantly reduces data size, transfer time, and processing time for DOCT imaging by a factor of eight. Specifically, these were reduced from 42 GB to 5.3 GB, 7 min to 55 s, and 4 hours to 30 min, respectively.

physics.optics↗

arXiv2026

Theoretical analysis of performance limitation of computational refocusing in optical coherence tomography

High-numerical-aperture optical coherence tomography (OCT) enables sub-cellular imaging but faces a trade-off between lateral resolution and depth of focus. Computational refocusing can correct defocus in Fourier-domain OCT, yet its limitations remain unaddressed theoretically. We formulate the lateral imaging process of OCT by using pupil-based imaging theory and the constraints of the computational refocusing in point-scanning OCT and spatially-coherent full-field OCT (FFOCT) are analyzed. The constrains in lateral sampling density and the confocality are considered, and it is shown that the maximum correctable defocus (MCD) is primarily limited by confocality in point-scanning OCT, while spatially-coherent FFOCT has no such constraint and can achieve virtually infinite MCD with a proper and reasonable sampling density. This makes spatially-coherent FFOCT particularly suitable for optical coherence microscopy.

physics.optics↗

arXiv2026

Dynamic full-field swept-source optical coherence microscope for cellular-resolution, long-depth, and intratissue-activity imaging

Optical coherence tomography (OCT) microscope (OCM) uses a high-numerical-aperture objective to achieve cellular-level lateral resolution. However, its practical imaging depth range is limited by the depth of focus (DOF). Although computational refocusing can potentially provide sharp images outside the DOF, signal reduction by the confocal effect still limits the imaging depth in practice in point-scanning OCT. In addition, standard OCT cannot visualize intra-tissue activities. To overcome these limitations, we demonstrated a spatially coherent full-field OCM (SC-FFOCM) with computational refocusing. In addition, a repetitive acquisition protocol was designed to visualize intra-tissue activities (i.e., dynamic OCT imaging). The in-focus lateral resolution is 1.4 um, and the axial resolution is 6.5 um (in air) at full-width at half-maximum intensity. Three-dimensional structure and the dynamic OCT imaging using SC-FFOCM with computational refocusing was applied to human breast adenocarcinoma spheroids (MCF-7 cell line). Volumetric dynamic imaging with cellular-level lateral resolution was demonstrated over the full depth of the spheroid.

physics.optics↗

arXiv2025

Dynamic optical coherence tomography algorithm for label-free assessment of swiftness and occupancy of intratissue moving scatterers

Dynamic optical coherence tomography (DOCT) statistically analyzes fluctuations in time-sequential OCT signals, enabling label-free and three-dimensional visualization of intratissue and intracellular activities. Current DOCT methods, such as logarithmic intensity variance (LIV) and OCT correlation decay speed (OCDS) have several limitations.Namely, the DOCT values and intratissue motions are not directly related, and hence DOCT values are not interpretable in the context of the tissue motility. We introduce a new DOCT algorithm that provides more direct interpretation of DOCT in the contexts of dynamic scatterer ratio and scatterer speed in the tissue.The detailed properties of the new and conventional DOCT methods are investigated by numerical simulations, and the experimental validation with in vitro and ex vivo samples demonstrates the feasibility of the new method.

physics.optics↗

arXiv2025

Image formation theory of optical coherence tomography with optical aberrations and its application for computational aberration correction

Computational corrections of defocus and aberrations in optical coherence tomography (OCT) offers a promising approach to realize high-resolution imaging with deep imaging depth, but without additional high hardware costs. However, these techniques are not well understood owing to a lack of accurate theoretical models and investigation tools. The image formation theory for OCT with optical aberrations is thus formulated here. Based on this theory, a numerical simulation method is developed, and computational refocusing and computational aberration correction (CAC) methods are designed. The CAC method based on the image formation theory is applied to simulated OCT signals and OCT images of a microparticle phantom and an in vivo human retina for simultaneous multi-depth correction of systematic aberration. The numerical simulation under the effective numerical aperture of 0.2 and 1.05 um central wavelength shows that the proposed method can obtain the Strehl ratios of more than 0.8 over a $\pm$ 100 um defocus range, while the conventional method cannot achieve this under the simulated conditions. Imaging results show that the CAC method designed based on the image formation theory can correct optical aberrations and improve the image quality more than the conventional CAC method. The proposed method improved the frequency component corresponding to the density of cone photoreceptors in OCT photoreceptor images by 1.2 to 1.4 times under the multi-depth correction. This theoretical model-based approach provides a powerful aid for understanding OCT imaging properties and processing method design.

physics.optics↗

arXiv2025

Dynamic-OCT simulation framework based on mathematical models of intratissue dynamics, image formation, and measurement noise

Dynamic optical coherence tomography (DOCT) enables label-free functional imaging by capturing temporal OCT signal variations caused by intracellular and intratissue motions. However, the relationship between DOCT signals and the sample motion behind them remains unclear. This paper presents a comprehensive DOCT simulation framework that incorporates mathematical models of intracellular/intratissue motions, two OCT signal generator types that generate OCT signal time sequences from the moving scatterer models, and representative DOCT algorithms. The theory and algorithms of the framework are described in detail, and the utility of this framework is demonstrated through numerical studies. This framework is available as open source and will enhance the understanding and utility of DOCT.

physics.med-ph↗

arXiv2025

Experimental and numerical investigation of wavelength and resolution dependency of dynamic optical coherence tomography signals

The wavelength and system-resolution dependencies of dynamic optical coherence tomography (DOCT) are investigated experimentally and numerically. Experimental investigations demonstrate significant wavelength dependency for the DOCT values but no resolution dependency. Numerical simulations were performed using diffusion, random-ballistic motion, and mono-directional flow-based motion models. Diffusion and random-ballistic motion-based simulations show significant wavelength dependency. Additionally, small but certain resolution dependency was revealed by these simulations. Mono-directional flow simulations did not show wavelength dependency, but did demonstrate resolution dependency. The DOCT value is sensitive to both tissue dynamics and the OCT system specification. These effects should be considered when interpreting DOCT images.

physics.optics↗

arXiv2025

Neural-network based high-speed volumetric dynamic optical coherence tomography

Wedemonstratedeep-learningneuralnetwork(NN)-baseddynamicopticalcoherence tomography (DOCT), which generates high-quality logarithmic-intensity-variance (LIV) DOCT images from only four OCT frames. The NN model is trained for tumor spheroid samples using a customized loss function: the weighted mean absolute error. This loss function enables highly accurate LIV image generation. The fidelity of the generated LIV images to the ground truth LIV images generated using 32 OCT frames is examined via subjective image observation and statistical analysis of image-based metrics. Fast volumetric DOCT imaging with an acquisition time of 6.55 s/volume is demonstrated using this NN-based method.

physics.med-ph↗

arXiv2025

Four-dimensional image formation theory of optical coherence tomography

We construct an accurate imaging theory for optical coherence tomography/microscopy (OCT/OCM) without approximations to calculate precise optical resolution and imaging characteristics. Our theory represents a broadband light source using a four-dimensional (4D) pupil function with a dimension for light frequency (reciprocal of wavelength) as the fourth axis in 4D frequency space. Consequently, 4D space-time representation is required in real space, connected to the 4D frequency space by a 4D Fourier transform. Our theory provides insight into a peculiar image formation in OCT/OCM, particularly when an apparatus has a high numerical aperture (NA) optical system to handle aberrations and dispersions simultaneously.

physics.optics↗

arXiv2025

Unified image formation theory for microscopy and optical coherence tomography in 4-D space-time

We construct an image formation theory that covers the majority of optical microscopy techniques that use diverse coherent or incoherent light-matter interactions. The theories of individual microscopy methods could not previously be connected with other systems because of the absence of a common theoretical framework. Using the general principles of quantum physics and applying a four-dimensional representation, we unify the image formation theories of optical systems ranging from classical microscopy to cutting-edge instruments into a single framework in which light is replaced with quantum fields and the interactions are represented using double-sided Feynman diagrams. Our universal methodology requires a four-dimensional aperture that enables sufficient understanding of the associations between the different imaging types and interprets image formation appropriately for all systems, including optical coherence tomography.

physics.optics↗

arXiv2024

Multiple scattering suppression for in vivo optical coherence tomography measurement using B-scan-wise multi-focus averaging method

We demonstrate a method that reduces the noise caused by multi-scattering (MS) photons in an \invivo optical coherence tomography image. This method combines a specially designed image acquisition (i.e., optical coherence tomography scan) scheme and subsequent complex signal processing. For the acquisition, multiple cross-sectional images (frames) are sequentially acquired while the depth position of the focus is altered for each frame by an electrically tunable lens. In the signal processing, the frames are numerically defocus-corrected, and complex averaged. Because of the inconsistency in the MS-photon trajectories among the different electrically tunable lens-induced defocus, this averaging reduces the MS signal. This method was validated using a scattering phantom and in vivo unanesthetized small fish samples, and was found to reduce MS noise even for unanesthetized in vivo measurement.

physics.optics↗

arXiv2024

Optical-coherence-tomography-based deep-learning scatterer-density estimator using physically accurate noise model

We demonstrate a deep-learning-based scatterer density estimator (SDE) that processes local speckle patterns of optical coherence tomography (OCT) images and estimates the scatterer density behind each speckle pattern. The SDE is trained using large quantities of numerically simulated OCT images and their associated scatterer densities. The numerical simulation uses a noise model that incorporates the spatial properties of three types of noise, i.e., shot noise, relative-intensity noise, and non-optical noise. The SDE's performance was evaluated numerically and experimentally using two types of scattering phantom and in vitro tumor spheroids. The results confirmed that the SDE estimates scatterer densities accurately. The estimation accuracy improved significantly when compared with our previous deep-learning-based SDE, which was trained using numerical speckle patterns generated from a noise model that did not account for the spatial properties of noise.

physics.bio-ph↗

arXiv2024

Polarization-artifact reduction and accuracy improvement of Jones-matrix polarization-sensitive optical coherence tomography by multi-focus averaging

Polarization-sensitive optical coherence tomography (PS-OCT) is a promising biomedical imaging tool for differentiation of various tissue properties. However, the presence of multiple-scattering (MS) signals can degrade the quantitative polarization measurement accuracy. We demonstrate a method to reduce MS signals and increase the measurement accuracy of Jones matrix PS-OCT. This method suppresses MS signals by averaging of multiple Jones matrix volumes measured using different focal positions. The MS signals are decorrelated among the volumes by focus position modulation and are thus reduced by averaging. However, the single scattering signals are kept consistent among the focus-modulated volumes by computational refocusing. We validated the proposed method using a scattering phantom and a postmortem medaka fish. The results showed reduced artifacts in birefringence and degree-of-polarization uniformity measurements, particularly in deeper regions in the samples. This method offers a practical solution to mitigate MS-induced artifacts in PS-OCT imaging and improves quantitative polarization measurement accuracy.

physics.optics↗

arXiv2023

Theoretical model for en face optical coherence tomography imaging and its application to volumetric differential contrast imaging

A new formulation of lateral imaging process of point-scanning optical coherence tomography (OCT) and a new differential contrast method designed by using this formulation are presented. The formulation is based on a mathematical sample model called the dispersed scatterer model (DSM), in which the sample is represented as a material with a spatially slowly varying refractive index and randomly distributed scatterers embedded in the material. It is shown that the formulation represents a meaningful OCT image and speckle as two independent mathematical quantities. The new differential contrast method is based on complex signal processing of OCT images, and the physical and numerical imaging processes of this method are jointly formulated using the same theoretical strategy as in the case of OCT. The formula shows that the method provides a spatially differential image of the sample structure. This differential imaging method is validated by measuring in vivo and in vitro samples.

physics.optics↗

arXiv2023

Label-free intratissue activity imaging of alveolar organoids with dynamic optical coherence tomography

An organoid is a three-dimensional (3D) in vitro cell culture emulating human organs. We applied 3D dynamic optical coherence tomography (DOCT) to visualize the intratissue and intracellular activities of human induced pluripotent stem cells (hiPSCs)-derived alveolar organoids in normal and fibrosis models. 3D DOCT data were acquired with an 840-nm spectral domain optical coherence tomography with axial and lateral resolutions of 3.8 μm (in tissue) and 4.9 μm, respectively. The DOCT images were obtained by the logarithmic-intensity-variance (LIV) algorithm, which is sensitive to the signal fluctuation magnitude. The LIV images revealed cystic structures surrounded by high-LIV borders and mesh-like structures with low LIV. The former may be alveoli with a highly dynamics epithelium, while the latter may be fibroblasts. The LIV images also demonstrated the abnormal repair of the alveolar epithelium.

physics.bio-ph↗