5 papers
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…
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…
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…
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…
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…