Abstract
We demonstrate a convolutional recurrent neural network-based volumetric imaging framework, termed Recurrent-MZ. Using a few 2D fluorescence microscopy images as its input, Recurrent-MZ provides a 50-fold extended depth-of-field in imaging of 3D fluorescent samples.
| Original language | English |
|---|---|
| Article number | STh2D.3 |
| Journal | Optics InfoBase Conference Papers |
| State | Published - 1 Jan 2021 |
| Externally published | Yes |
| Event | CLEO: Science and Innovations, CLEO:S and I 2021 - Part of Conference on Lasers and Electro-Optics, CLEO 2021 - Virtual, Online, United States Duration: 9 May 2021 → 14 May 2021 |
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Mechanics of Materials
Fingerprint
Dive into the research topics of 'Volumetric fluorescence microscopy using convolutional recurrent neural networks'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver