English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Three-dimensional fluorescence microscopy often suffers from anisotropy,where the resolution along the axial direction is lower than that within thelateral imaging plane. We address this issue by presenting Dual-Cycle, a newframework for joint deconvolution and fusion of dual-view fluorescence images.Inspired by the recent Neuroclear method, Dual-Cycle is designed as acycle-consistent generative network trained in a self-supervised fashion bycombining a dual-view generator and prior-guided degradation model. We validateDual-Cycle on both synthetic and real data showing its state-of-the-artperformance without any external training data.

Dual-Cycle: Self-Supervised Dual-View Fluorescence Microscopy Image Reconstruction using CycleGAN