Automated and rapid target position alignment in laser–plasma experiments using deep learning algorithms-Reference-Cited by-同舟云学术

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Automated and rapid target position alignment in laser–plasma experiments using deep learning algorithms

Published:2024-09 Issue: Volume:1066 Page:169641
ISSN:0168-9002
Container-title:Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
language:en
Short-container-title:Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

Author:

Guo Zhen^ORCID,Xia Yadong,He Qiangyou,Li Fangnan,Chen Ke,Zang Mengxuan,Wang Qiang,Guo Enshuo,Yan Xueqing,Lin Chen

Funder

National Key Scientific Instrument and Equipment Development Projects of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference43 articles.

1. Forward ion acceleration in thin films driven by a high-intensity laser;Maksimchuk;Phys. Rev. Lett.,2000

2. Above-100 MeV proton beam generation from near-critical-density plasmas irradiated by moderate Laguerre–Gaussian laser pulses;Hu;Plasma Phys. Control. Fusion,2022

3. Towards clinical translation of FLASH radiotherapy;Vozenin;Nat. Rev. Clin. Oncol.,2022

4. Association of cancer stem cell radio-resistance under ultra-high dose rate FLASH irradiation with lysosome-mediated autophagy;Yang;Front. Cell Dev. Biol.,2021

5. Ultra-high dose rate FLASH irradiation induced radio-resistance of normal fibroblast cells can be enhanced by hypoxia and mitochondrial dysfunction resulting from loss of cytochrome c;Han;Front. Cell Dev. Biol.,2021

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