arXiv subjects

Juyeon Park

Publications and source records attributed to Juyeon Park.

6 recordsLinked to original sources

arXiv2025

Morphology-Preserving Holotomography: Quantitative Analysis of 3D Organoid Dynamics

Organoids are three-dimensional (3D) in vitro models for studying tissue development, disease progression, and physiological responses. Holotomography (HT) enables long-term, label-free imaging of live organoids by reconstructing volumetric refractive-index (RI) maps, but quantitative analysis is limited by the missing-cone artifact, which introduces anisotropic resolution and axial distortion. Here, we present a quantitative analysis framework that addresses the missing-cone problem at the level of image representation rather than reconstruction. We introduce morphology-preserving holotomography (MP-HT), a torus-shaped spatial filtering strategy that emphasizes high-spatial-frequency RI texture while suppressing low-frequency components most susceptible to missing-cone-induced distortion. Based on MP-HT, we develop a 3D segmentation pipeline for robust separation of epithelial and luminal structures, together with a model-based RI quantification approach that incorporates the system point spread function to enable morphology-independent estimation of dry-mass density and total dry mass. We apply the framework to long-term imaging of live hepatic organoids undergoing expansion, collapse, and fusion. The results demonstrate consistent segmentation across diverse geometries and reveal coordinated epithelial-lumen remodeling, breakdown of morphometric homeostasis during collapse, and transient biophysical fluctuations during fusion. Overall, this work establishes a physically transparent and reproducible approach for quantitative, label-free analysis of organoid dynamics in three dimensions.

physics.med-ph↗

arXiv2025

Refractive Index-Correlated Pseudocoloring for Adaptive Color Fusion in Holotomographic Cytology

Conventional bright-field (BF) cytology of thyroid fine-needle aspiration biopsy (FNAB) suffers from staining variability and limited subcellular contrast. Here, we present a refractive index-correlated pseudocoloring (RICP) framework that integrates quantitative refractive index (RI) maps obtained by holotomography (HT) with color BF images to enhance diagnostic interpretability. The imaging platform combines a digital micromirror device (DMD)-based HT system with an RGB LED illumination module, enabling simultaneous acquisition of RI tomograms and BF images from PAP-stained thyroid samples. The RICP algorithm adaptively embeds RI-derived structural information into the least-occupied hue channel, preserving color fidelity while enhancing nuclear and cytoplasmic contrast. Applied to benign and malignant thyroid clusters, RICP revealed diagnostically relevant features such as nucleoli, lipid droplets, and nuclear irregularities, and hue-saturation analysis quantitatively differentiated cytological categories. This perceptually grounded, label-free framework bridges conventional color cytology and quantitative optical imaging for improved diagnostic precision.

physics.optics↗

arXiv2025

Pupil Phase Series: A Fast, Accurate, and Energy-Conserving Model for Forward and Inverse Light Scattering in Thick Biological Samples

We present the pupil phase series (PPS), a fast and accurate forward scattering algorithm for simulating and inverting multiple light scattering in large biological samples. PPS achieves high-angle scattering accuracy and energy conservation simultaneously by introducing a spatially varying phase modulation in the pupil plane. By expanding the scattering term into a Taylor series, PPS achieves high precision while maintaining computational efficiency. We integrate PPS into a quasi-Newton inverse solver to reconstruct the three-dimensional refractive index of a 180 um-thick human organoid. Compared to linear reconstruction, our method recovers subcellular features-such as nuclei and vesicular structures-deep within the sample volume. PPS offers a scalable and interpretable alternative to conventional solvers, paving the way for high-throughput, label-free imaging of optically thick biological tissues.

physics.optics↗

arXiv2025

Compression benchmarking of holotomography data using the OME-Zarr storage format

Holotomography (HT) is a label-free, three-dimensional imaging technique that captures refractive index distributions of biological samples at sub-micron resolution. As modern HT systems enable high-throughput and large-scale acquisition, they produce terabyte-scale datasets that require efficient data management. This study presents a systematic benchmarking of data compression strategies for HT data stored in the OME-Zarr format, a cloud-compatible, chunked data structure suitable for scalable imaging workflows. Using representative datasets-including embryo, tissue, and birefringent tissue volumes-we evaluated combinations of preprocessing filters and 25 compression configurations across multiple compression levels. Performance was assessed in terms of compression ratio, bandwidth, and decompression speed. A throughput-based evaluation metric was introduced to simulate real-world conditions under varying network constraints, supporting optimal compressor selection based on system bandwidth. The results offer practical guidance for storage and transmission of large HT datasets and serve as a reference for implementing scalable, FAIR-aligned imaging workflows in cloud and high-performance computing environments.

physics.optics↗

arXiv2024

Unsupervised Outlier Detection using Random Subspace and Subsampling Ensembles of Dirichlet Process Mixtures

Probabilistic mixture models are recognized as effective tools for unsupervised outlier detection owing to their interpretability and global characteristics. Among these, Dirichlet process mixture models stand out as a strong alternative to conventional finite mixture models for both clustering and outlier detection tasks. Unlike finite mixture models, Dirichlet process mixtures are infinite mixture models that automatically determine the number of mixture components based on the data. Despite their advantages, the adoption of Dirichlet process mixture models for unsupervised outlier detection has been limited by challenges related to computational inefficiency and sensitivity to outliers in the construction of outlier detectors. Additionally, Dirichlet process Gaussian mixtures struggle to effectively model non-Gaussian data with discrete or binary features. To address these challenges, we propose a novel outlier detection method that utilizes ensembles of Dirichlet process Gaussian mixtures. This unsupervised algorithm employs random subspace and subsampling ensembles to ensure efficient computation and improve the robustness of the outlier detector. The ensemble approach further improves the suitability of the proposed method for detecting outliers in non-Gaussian data. Furthermore, our method uses variational inference for Dirichlet process mixtures, which ensures both efficient and rapid computation. Empirical analyses using benchmark datasets demonstrate that our method outperforms existing approaches in unsupervised outlier detection.

cs.LG↗

arXiv2023

Single-shot refractive index slice imaging using spectrally multiplexed optical transfer function reshaping

The refractive index (RI) of cells and tissues is crucial in pathophysiology as a noninvasive and quantitative imaging contrast. Although its measurements have been demonstrated using three-dimensional quantitative phase imaging methods, these methods often require bulky interferometric setups or multiple measurements, which limits the measurement sensitivity and speed. Here, we present a single-shot RI imaging method that visualizes the RI of the in-focus region of a sample. By exploiting spectral multiplexing and optical transfer function engineering, three color-coded intensity images of a sample with three optimized illuminations were simultaneously obtained in a single-shot measurement. The measured intensity images were then deconvoluted to obtain the RI image of the in-focus slice of the sample. As a proof of concept, a setup was built using Fresnel lenses and a liquid-crystal display. For validation purposes, we measured microspheres of known RI and cross-validated the results with simulated results. Various static and highly dynamic biological cells were imaged to demonstrate that the proposed method can conduct single-shot RI slice imaging of biological samples with subcellular resolution.

physics.optics↗