Phase Mask-Based Multimodal Superresolution Microscopy

被引:10
|
作者
Beams, Ryan [1 ]
Woodcock, Jeremiah W. [1 ]
Gilman, Jeffrey W. [1 ]
Stranick, Stephan J. [1 ]
机构
[1] NIST, Mat Measurement Lab, 100 Bur Dr, Gaithersburg, MD 20899 USA
关键词
microscopy; superresolution; nonlinear microscopy; 2-PHOTON EXCITATION MICROSCOPY; TORALDO FILTERS; DIFFRACTION; RESOLUTION; LIGHT; LIMIT; FIELD;
D O I
10.3390/photonics4030039
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
We demonstrate a multimodal superresolution microscopy technique based on a phase masked excitation beam in combination with spatially filtered detection. The theoretical foundation for calculating the focus from a non-paraxial beam with an arbitrary azimuthally symmetric phase mask is presented for linear and two-photon excitation processes as well as the theoretical resolution limitations. Experimentally this technique is demonstrated using two-photon luminescence from 80nm gold particle as well as two-photon fluorescence lifetime imaging of fluorescent polystyrene beads. Finally to illustrate the versatility of this technique we acquire two-photon fluorescence lifetime, two-photon luminescence, and second harmonic images of a mixture of fluorescent molecules and 80nm gold particles with < 120nm resolution (l /7). Since this approach exclusively relies on engineering the excitation and collection volumes, it is suitable for a wide range of scanning-based microscopies.
引用
收藏
页数:12
相关论文
共 50 条
  • [41] Components loss for neural networks in mask-based speech enhancement
    Xu, Ziyi
    Elshamy, Samy
    Zhao, Ziyue
    Fingscheidt, Tim
    EURASIP JOURNAL ON AUDIO SPEECH AND MUSIC PROCESSING, 2021, 2021 (01)
  • [42] Photopolymerization of Thick Layers of Compositions for Mask-Based Stereolithographic Synthesis
    Chesnokov, S. A.
    Chechet, Yu, V
    Yudin, V. V.
    Abakumov, G. A.
    HIGH ENERGY CHEMISTRY, 2019, 53 (05) : 413 - 417
  • [43] Components loss for neural networks in mask-based speech enhancement
    Ziyi Xu
    Samy Elshamy
    Ziyue Zhao
    Tim Fingscheidt
    EURASIP Journal on Audio, Speech, and Music Processing, 2021
  • [44] Moving Object Tracking Using Symmetric Mask-Based Scheme
    Hsia, Chih-Hsien
    Huang, Ding-Wei
    Chiang, Jen-Shiun
    Wu, Zong-Jheng
    FIFTH INTERNATIONAL CONFERENCE ON INFORMATION ASSURANCE AND SECURITY, VOL 1, PROCEEDINGS, 2009, : 173 - 176
  • [45] Depth from Defocus on a Transmissive Diffraction Mask-based Sensor
    Kunnath, Neeth
    Cho, Ji-Ho
    Langer, Michael
    2020 17TH CONFERENCE ON COMPUTER AND ROBOT VISION (CRV 2020), 2020, : 214 - 221
  • [46] Mask-based second-generation connectivity and attribute filters
    Ouzounis, Georgios K.
    Wilkinson, Michael H. F.
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2007, 29 (06) : 990 - 1004
  • [47] Mask-based blind source separation and MVDR beamforming in ASR
    Renke He
    Yanhua Long
    Yijie Li
    Jiaen Liang
    International Journal of Speech Technology, 2020, 23 : 133 - 140
  • [48] Improvement of Mask-Based Speech Source Separation Using DNN
    Zhan, Ge
    Huang, Zhaoqiong
    Ying, Dongwen
    Pan, Jielin
    Yan, Yonghong
    2016 10TH INTERNATIONAL SYMPOSIUM ON CHINESE SPOKEN LANGUAGE PROCESSING (ISCSLP), 2016,
  • [49] Toward Depth hstimation Using Mask-Based Lensless Cameras
    Asif, M. Salman
    2017 FIFTY-FIRST ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS, 2017, : 1467 - 1470
  • [50] DeepLIR: Attention-based approach for Mask-Based Lensless Image Reconstruction
    Poudel, Arpan
    Nakarmi, Ukash
    2024 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION WORKSHOPS, WACVW 2024, 2024, : 431 - 439