activity
20182026
most citedHoloStain: Holographic virtual staining of individual biological cells

106 citations · 539 across the 18 of their papers we have counts for

collaborators

18 papers

cs.CV2026

PRISM: Distribution-Gated Flow Matching for Controllable Unpaired Image Translation

Elad Yoshai, Natan T. Shaked

Unpaired image-to-image translation must decide, per image, what to change and what to preserve without paired supervision. Many diffusion-based unpaired translators control preser…

cs.CV2026

CAFlow: Adaptive-Depth Single-Step Flow Matching for Efficient Histopathology Super-Resolution

Elad Yoshai, Ariel D. Yoshai, Natan T. Shaked

In digital pathology, whole-slide images routinely exceed gigapixel resolution, making computationally intensive generative super-resolution (SR) impractical for routine deployment…

eess.IV2025

Hierarchical Sparse Attention Framework for Computationally Efficient Classification of Biological Cells

Elad Yoshai, Dana Yagoda-Aharoni, Eden Dotan +1

We present SparseAttnNet, a new hierarchical attention-driven framework for efficient image classification that adaptively selects and processes only the most informative pixels fr…

eess.IV2024

Enhancing frozen histological section images using permanent-section-guided deep learning with nuclei attention

Elad Yoshai, Gil Goldinger, Miki Haifler +1

In histological pathology, frozen sections are often used for rapid diagnosis during surgeries, as they can be produced within minutes. However, they suffer from artifacts and ofte…

eess.IV2023

Super resolution of histopathological frozen sections via deep learning preserving tissue structure

Elad Yoshai, Gil Goldinger, Miki Haifler +1

Histopathology plays a pivotal role in medical diagnostics. In contrast to preparing permanent sections for histopathology, a time-consuming process, preparing frozen sections is s…

physics.bio-ph2021★ 87 cited

Real-time stain-free classification of cancer cells and blood cells using interferometric phase microscopy and machine learning

Noga Nissim, Matan Dudaie, Itay Barnea. +1

We present a method for a real time visualization and automatic processing for detection and classification of untouched cancer cells in blood during stain free imaging flow cytome…

physics.bio-ph2020

High-resolution 4D acquisition of freely swimming human sperm cells without staining

Gili Dardikman-Yoffe, Simcha K. Mirsky, Itay Barnea +1

We present a new acquisition method that enables high-resolution, fine-detail full reconstruction of the three-dimensional movement and structure of individual human sperm cells sw…

physics.bio-ph2019★ 106 cited

HoloStain: Holographic virtual staining of individual biological cells

Yoav N. Nygate, Mattan Levi, Simcha K. Mirsky +6

Many medical and biological protocols for analyzing individual biological cells involve morphological evaluation based on cell staining, designed to enhance imaging contrast and en…

physics.bio-ph2019★ 30 cited

Integral refractive index imaging of flowing cell nuclei using quantitative phase microscopy combined with fluorescence microscopy

Gili Dardikman, Yoav N. Nygate, Itay Barnea +4

We suggest a new multimodal imaging technique for quantitatively measuring the integral (thickness-average) refractive index of the nuclei of live biological cells in suspension. F…

physics.optics2019★ 10 cited

Four dimensional phase unwrapping of dynamic objects in digital holography

Gili Dardikman, Gyanendra Singh, Natan T. Shaked

We present a new four-dimensional phase unwrapping approach for time-lapse quantitative phase microscopy, which allows reconstruction of optically thick objects that are optically…

physics.optics2019★ 43 cited

Review on methods of solving the refractive index-thickness coupling problem in digital holographic microscopy of biological cells

Gili Dardikman, Natan T. Shaked

Digital holographic microscopy is a thriving imaging modality that attracted considerable research interest in quantitative biological cell imaging due to its ability to not only c…

physics.optics2019★ 28 cited

Simultaneous off-axis multiplexed holography and regular fluorescence microscopy of biological cells

Yoav N. Nygate, Gyanendra Singh, Itay Barnea +1

We present a new technique for obtaining simultaneous multimodal quantitative phase and fluorescence microscopy of biological cells, providing both quantitative phase imaging and m…

physics.optics2019★ 70 cited

Six-pack off-axis holography

Moran Rubin, Gili Dardikman, Simcha K. Mirsky +2

We present a new holographic concept, named six-pack holography (6PH), in which we compress six off-axis holograms into a single multiplexed off-axis hologram without loss of magni…

physics.optics2019★ 67 cited

Simultanous two-wavelength phase unwrapping using external module for multiplexing off-axis holography

Nir A. Turko, Natan T. Shaked

We present a dual-wavelength external holographic microscopy module for quantitative phase imaging of 3D structures with extended thickness range. This is done by simultaneous acqu…

physics.optics2019★ 35 cited

Is multiplexed off-axis holography for quantitative phase imaging more spatial bandwidth-efficient than on-axis holography?

Gili Dardikman, Natan T. Shaked

Digital holographic microcopy is a thriving imaging modality that attracts considerable research interest due to its ability to not only create excellent label-free contrast, but a…

physics.optics2019★ 20 cited

Single-exposure full-field multi-depth imaging using low-coherence holographic multiplexing

Lauren Wolbromsky, Nir A. Turko, Natan T. Shaked

We present a new interferometric imaging approach that allows for multiple-depth imaging in a single acquisition, using off-axis low-coherence holographic multiplexing. This techni…

physics.optics2019★ 43 cited

Simultaneous three-wavelength unwrapping using external digital holographic multiplexing module

Nir A. Turko, Pinkie Jacob Eravuchira, Itay Barnea +1

We present an external interferometric setup that is able to simultaneously acquire three wavelengths of the same sample instance without scanning or multiple exposures. This setup…

eess.IV2018

TOP-GAN: Label-Free Cancer Cell Classification Using Deep Learning with a Small Training Set

Moran Rubin, Omer Stein, Nir A. Turko +6

We propose a new deep learning approach for medical imaging that copes with the problem of a small training set, the main bottleneck of deep learning, and apply it for classificati…