arXiv subjects

Satoshi Matsusaka

Publications and source records attributed to Satoshi Matsusaka.

9 recordsLinked to original sources

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

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

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↗

arXiv2025

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

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↗

arXiv2024

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↗

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↗

arXiv2022

Label-free drug response evaluation of human derived tumor spheroids using three-dimensional dynamic optical coherence tomography

We demonstrate label-free drug response evaluations of human breast (MCF-7) and colon (HT-29) cancer spheroids via dynamic optical coherence tomography (OCT). The MCF-7 and HT-29 spheroids were treated with paclitaxel (PTX, or Taxol) and the active metabolite of irinotecan (SN-38), respectively. The drugs were applied using 0 (control), 0.1, 1, and 10 uM concentrations with treatment times of 1, 3, and 6 days. The samples were scanned using a repeated raster scan protocol and two dynamic OCT algorithms, logarithmic intensity variance (LIV) and late OCT correlation decay speed (OCDSl) analyses, were applied to visualize the tissue and cellular dynamics. Different drug response patterns of the two spheroid types were visualized clearly and analyzed quantitatively by LIV and OCDSl imaging. For both spheroid types, structural corruptions and reduction of LIV and OCDSl were observed. These results may indicate different mechanisms of the drug action. The results suggest that dynamic OCT can be used to highlight drug response patterns and perform anti-cancer drug testing.

physics.med-ph↗