1.35ns SBS laser pulse

Liu, Hongxin; Li, Yongliang; Chao, Yang; Gu, Xiaokun; Hu, Weiwei; Zhang, Yipeng; Zhang, Yingming

doi:10.1016/j.ijleo.2019.04.123

Cited by 4 publications

(3 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hon et al proposed and practically realized the pulse duration compression of SBS in gas and used CH 4 gas to compress the pump pulse duration from 20 ns to 3 ns in the tapered waveguide structure [17]. Liu et al employed a focused single-cell structure to compress the pump pulse from 8.05 ns and 145 mJ to 1.35 ns and 94.5 mJ, and the energy efficiency reached 65% [18]. SBS pulse compression technology can compress nanosecond laser pulses to sub-nanosecond levels.…”

Section: Introductionmentioning

confidence: 99%

Pulse Duration Compression by Two-Stage Stimulated Brillouin Scattering and Stimulated Raman Scattering

Han,

Liu,

et al. 2024

Photonics

View full text Add to dashboard Cite

A pulse duration compression technique that combines stimulated Brillouin scattering (SBS) and stimulated Raman scattering (SRS) was presented in this study, achieving an output pulse duration of 48.3 ps. The feasibility of this approach has been experimentally demonstrated. To be specific, a pulse duration of 7.4 ns is compressed to 48.3 ps with an energy of 5.27 mJ, and the energy efficiency of the SRS pulse duration compression system is up to 21.84%. Moreover, this study provides a practical method for reliably generating high-energy short pulses.

show abstract

Section: Introductionmentioning

confidence: 99%

Pulse Duration Compression by Two-Stage Stimulated Brillouin Scattering and Stimulated Raman Scattering

Han,

Liu,

et al. 2024

Photonics

View full text Add to dashboard Cite

show abstract

“…[ 13 ] combines distance transforms for single cell nuclei with discrete boundaries. A center vector encoding which is aimed to be more robust to label inconsistencies is proposed in [ 14 ], whereas in [ 15 ], horizontal and vertical gradient maps are used. To improve the generalization ability of a model for cell types with only few or no annotated images, a generative adversarial network-based image style transfer to generate augmented training samples of that cell types has been used in [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

Cell segmentation and tracking using CNN-based distance predictions and a graph-based matching strategy

et al. 2020

View full text Add to dashboard Cite

The accurate segmentation and tracking of cells in microscopy image sequences is an important task in biomedical research, e.g., for studying the development of tissues, organs or entire organisms. However, the segmentation of touching cells in images with a low signal-to-noise-ratio is still a challenging problem. In this paper, we present a method for the segmentation of touching cells in microscopy images. By using a novel representation of cell borders, inspired by distance maps, our method is capable to utilize not only touching cells but also close cells in the training process. Furthermore, this representation is notably robust to annotation errors and shows promising results for the segmentation of microscopy images containing in the training data underrepresented or not included cell types. For the prediction of the proposed neighbor distances, an adapted U-Net convolutional neural network (CNN) with two decoder paths is used. In addition, we adapt a graph-based cell tracking algorithm to evaluate our proposed method on the task of cell tracking. The adapted tracking algorithm includes a movement estimation in the cost function to re-link tracks with missing segmentation masks over a short sequence of frames. Our combined tracking by detection method has proven its potential in the IEEE ISBI 2020 Cell Tracking Challenge (http://celltrackingchallenge.net/) where we achieved as team KIT-Sch-GE multiple top three rankings including two top performances using a single segmentation model for the diverse data sets.

show abstract

“…For years, detailed research works on SBS-based pulse compression technology had been hotly pursued by several groups. Although many overviews on the research progress of SBS media have been reviewed, there are few reports on summarizing the structures of SBS pulse compressors [45,46]. In this paper, recent research progress using different SBS pulse compression structures for picosecond pulse generation were reviewed.…”

Section: Introductionmentioning

confidence: 99%

Developments of Picosecond Lasers Based on Stimulated Brillouin Scattering Pulse Compression

et al. 2021

View full text Add to dashboard Cite

Pulse compression based on stimulated Brillouin scattering (SBS) is a nonlinear optical approach that efficiently converts high-energy nanosecond pulses into the picosecond. Since the first observation of SBS pulse compression, different compression structures for different input and output parameters were developed to optimize the characteristics of pulse compression in the past decades. Here, a comprehensive review of the development status of SBS pulse compression schemes is provided, meanwhile, methods and trends to the optimization of SBS pulse compression are proposed.

show abstract

1.35ns SBS laser pulse

Cited by 4 publications

References 23 publications

Pulse Duration Compression by Two-Stage Stimulated Brillouin Scattering and Stimulated Raman Scattering

Pulse Duration Compression by Two-Stage Stimulated Brillouin Scattering and Stimulated Raman Scattering

Cell segmentation and tracking using CNN-based distance predictions and a graph-based matching strategy

Developments of Picosecond Lasers Based on Stimulated Brillouin Scattering Pulse Compression

Contact Info

Product

Resources

About