Your browser doesn't support javascript.
loading
Shot-Noise Limited Nonlinear Optical Imaging Excited With GHz Femtosecond Pulses and Denoised by Deep-Learning.
Wang, Wenlong; Wen, Junpeng; Sheng, Yuke; Wei, Chiyi; Kong, Cihang; Liu, Yalong; Wei, Xiaoming; Yang, Zhongmin.
Afiliación
  • Wang W; School of Physics and Optoelectronics, South China University of Technology, Guangzhou, China.
  • Wen J; State Key Laboratory of Luminescent Materials and Devices and Institute of Optical Communication Materials, South China University of Technology, Guangzhou, China.
  • Sheng Y; Guangdong Engineering Technology Research and Development Center of Special Optical Fiber Materials and Devices, South China University of Technology, Guangzhou, China.
  • Wei C; Guangdong Provincial Key Laboratory of Fiber Laser Materials and Applied Techniques, South China University of Technology, Guangzhou, China.
  • Kong C; Research Institute of Future Technology, South China University of Technology, Guangzhou, China.
  • Liu Y; School of Physics and Optoelectronics, South China University of Technology, Guangzhou, China.
  • Wei X; State Key Laboratory of Luminescent Materials and Devices and Institute of Optical Communication Materials, South China University of Technology, Guangzhou, China.
  • Yang Z; Guangdong Engineering Technology Research and Development Center of Special Optical Fiber Materials and Devices, South China University of Technology, Guangzhou, China.
J Biophotonics ; : e202400186, 2024 Sep 01.
Article en En | MEDLINE | ID: mdl-39218434
ABSTRACT
Multiphoton fluorescence microscopy excited with femtosecond pulses at high repetition rates, particularly in the range of 100's MHz to GHz, offers an alternative solution to suppress photoinduced damage to biological samples, for example, photobleaching. Here, we demonstrate the use of a U-Net-based deep-learning algorithm for suppressing the inherent shot noise of the two-photon fluorescence images excited with GHz femtosecond pulses. With the trained denoising neural network, the image quality of the representative two-photon fluorescence images of the biological samples is shown to be significantly improved. Moreover, for input raw images with even SNR reduced to -4.76 dB, the trained denoising network can recover the main image structure from noise floor with acceptable fidelity and spatial resolution. It is anticipated that the combination of GHz femtosecond pulses and deep-learning denoising algorithm can be a promising solution for eliminating the trade-off between photoinduced damage and image quality in nonlinear optical imaging platforms.
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Biophotonics Asunto de la revista: BIOFISICA Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Alemania
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Biophotonics Asunto de la revista: BIOFISICA Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Alemania