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EventLFM: event camera integrated Fourier light field microscopy for ultrafast 3D imaging.
Guo, Ruipeng; Yang, Qianwan; Chang, Andrew S; Hu, Guorong; Greene, Joseph; Gabel, Christopher V; You, Sixian; Tian, Lei.
Afiliação
  • Guo R; Department of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA.
  • Yang Q; Department of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA.
  • Chang AS; Department of Physiology and Biophysics, Boston University, Boston, MA, 02215, USA.
  • Hu G; Department of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA.
  • Greene J; Department of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA.
  • Gabel CV; Department of Physiology and Biophysics, Boston University, Boston, MA, 02215, USA.
  • You S; Neurophotonics Center, Boston University, Boston, MA, 02215, USA.
  • Tian L; Research Laboratory of Electronics (RLE) in the Department of Electrical Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Light Sci Appl ; 13(1): 144, 2024 Jun 26.
Article em En | MEDLINE | ID: mdl-38918363
ABSTRACT
Ultrafast 3D imaging is indispensable for visualizing complex and dynamic biological processes. Conventional scanning-based techniques necessitate an inherent trade-off between acquisition speed and space-bandwidth product (SBP). Emerging single-shot 3D wide-field techniques offer a promising alternative but are bottlenecked by the synchronous readout constraints of conventional CMOS systems, thus restricting data throughput to maintain high SBP at limited frame rates. To address this, we introduce EventLFM, a straightforward and cost-effective system that overcomes these challenges by integrating an event camera with Fourier light field microscopy (LFM), a state-of-the-art single-shot 3D wide-field imaging technique. The event camera operates on a novel asynchronous readout architecture, thereby bypassing the frame rate limitations inherent to conventional CMOS systems. We further develop a simple and robust event-driven LFM reconstruction algorithm that can reliably reconstruct 3D dynamics from the unique spatiotemporal measurements captured by EventLFM. Experimental results demonstrate that EventLFM can robustly reconstruct fast-moving and rapidly blinking 3D fluorescent samples at kHz frame rates. Furthermore, we highlight EventLFM's capability for imaging of blinking neuronal signals in scattering mouse brain tissues and 3D tracking of GFP-labeled neurons in freely moving C. elegans. We believe that the combined ultrafast speed and large 3D SBP offered by EventLFM may open up new possibilities across many biomedical applications.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article