7 March 2016 Scan-less, line-field confocal microscopy by combination of wavelength/space conversion with dual optical comb
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Abstract
Optical frequency comb (OFC) has attracted attentions for optical frequency metrology in visible and infrared regions because the mode-resolved OFC spectrum can be used as a precise frequency ruler due to both characteristics of broadband radiation and narrow-line CW radiation. Furthermore, the absolute accuracy of all frequency modes in OFC is secured by phase-locking a repetition frequency frep and a carrier-envelope-offset frequency fceo to a frequency standard. However, application fields of OFC other than optical frequency metrology are still undeveloped. One interesting aspect of OFC except for the frequency ruler is optical carrier having a huge number of discrete frequency channels because OFC is composed of a series of frequency spikes regularly separated by frep in the broad spectral range. If a certain quantity to be measured is encoded on each comb mode by dimensional conversion, a huge number of data for the measured quantity can be obtained from a single mode-resolved spectrum of OFC. In this paper, we encode the confocal microscopic line-image of a sample on the mode-resolved OFC spectrum by the dimensional conversion between wavelength and 1D-space. The resulting image-encoded OFC spectrum is acquired by an optical spectrum analyzer or dual comb spectrometer. Finally, the line image of the sample is decoded from the spectral amplitude of the mode-resolved OFC spectrum. The combination of OFC with the dimensional conversion enables to establish both confocal modality and line-field imaging under the scan-less condition.
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Takeshi Yasui, Takeshi Yasui, Eiji Hase, Eiji Hase, Shuji Miyamoto, Shuji Miyamoto, Yi-Da Hsieh, Yi-Da Hsieh, Takeo Minamikawa, Takeo Minamikawa, Hirotsugu Yamamoto, Hirotsugu Yamamoto, "Scan-less, line-field confocal microscopy by combination of wavelength/space conversion with dual optical comb", Proc. SPIE 9720, High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management, 972006 (7 March 2016); doi: 10.1117/12.2213560; https://doi.org/10.1117/12.2213560
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