106 citations · 539 across the 18 of their papers we have counts for
4 papers · 1 filter
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…
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…