Reassignment of Scattered Emission Photons in Multifocal Multiphoton Microscopy
Name
Cha-2014-Reassignment of scattered.pdf
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9.64 MB
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Author(s)
Cha, Jae Won
Singh, Vijay Raj
Kim, Ki Hean
Subramanian, Jaichandar
Peng, Qiwen
Yu, Hanry
Nedivi, Elly
So, Peter T. C.
Date Issued
June 2014
Journal
Scientific Reports
Publisher
Nature Publishing Group
Citation
Cha, Jae Won, Vijay Raj Singh, Ki Hean Kim, Jaichandar Subramanian, Qiwen Peng, Hanry Yu, Elly Nedivi, and Peter T. C. So. “Reassignment of Scattered Emission Photons in Multifocal Multiphoton Microscopy.” Sci. Rep. 4 (June 5, 2014).
Version
Final published version
Abstract
Multifocal multiphoton microscopy (MMM) achieves fast imaging by simultaneously scanning multiple foci across different regions of specimen. The use of imaging detectors in MMM, such as CCD or CMOS, results in degradation of image signal-to-noise-ratio (SNR) due to the scattering of emitted photons. SNR can be partly recovered using multianode photomultiplier tubes (MAPMT). In this design, however, emission photons scattered to neighbor anodes are encoded by the foci scan location resulting in ghost images. The crosstalk between different anodes is currently measured a priori, which is cumbersome as it depends specimen properties. Here, we present the photon reassignment method for MMM, established based on the maximum likelihood (ML) estimation, for quantification of crosstalk between the anodes of MAPMT without a priori measurement. The method provides the reassignment of the photons generated by the ghost images to the original spatial location thus increases the SNR of the final reconstructed image.
MIT Department
Massachusetts Institute of Technology. Center for Biomedical Engineering
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Department of Mechanical Engineering
Picower Institute for Learning and Memory
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Creative Commons Attribution-NonCommercial-ShareAlike 3.0
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DOI of Published Version
https://doi.org/10.1038/srep05153
