Abstract
Recent developments using deep learning (DL) super-resolution in structured-illumination microscopy (SIM) have improved speed in two-dimensional (2D) image restoration and minimized the impact of noise. We explore extending this 2D DL technique to 3D by augmenting the 2D-convolutional layers to 3D in a U-Net DL network. We demonstrate experimentally that this extension improves lateral and axial resolution in the final 3D restoration compared to the resolution achieved by axially stacking the outputs of the 2D U-Net.
© 2023 The Author(s)
PDF Article | Presentation VideoMore Like This
S. Parisa Dajkhosh, Mazharul Hossain, and Chrysanthe Preza
JTu4A.42 3D Image Acquisition and Display: Technology, Perception and Applications (3D) 2023
Ankit Butola, Sebastian Acuna, Daniel Henry Hansen, and Krishna Agarwal
126300L European Conference on Biomedical Optics (ECBO) 2023
Henning Ortkrass, Jasmin Schürstedt, Gerd Wiebusch, Karolina Szafranska, Peter McCourt, and Thomas Huser
ch_p_28 The European Conference on Lasers and Electro-Optics (CLEO/Europe) 2023