Deep learning enables reference-free isotropic super-resolution for volumetric fluorescence microscopy

no code implementations • 19 Apr 2021 • Hyoungjun Park, Myeongsu Na, Bumju Kim, Soohyun Park, Ki Hean Kim, Sunghoe Chang, Jong Chul Ye

Volumetric imaging by fluorescence microscopy is often limited by anisotropic spatial resolution from inferior axial resolution compared to the lateral resolution.

Generative Adversarial Network Super-Resolution

CycleGAN with a Blur Kernel for Deconvolution Microscopy: Optimal Transport Geometry

no code implementations • 26 Aug 2019 • Sungjun Lim, Hyoungjun Park, Sang-Eun Lee, Sunghoe Chang, Jong Chul Ye

Deconvolution microscopy has been extensively used to improve the resolution of the wide-field fluorescent microscopy, but the performance of classical approaches critically depends on the accuracy of a model and optimization algorithms.

Generative Adversarial Network Image Deconvolution