Physically-based in silico light sheet microscopy for visualizing fluorescent brain models

Marwan Abdellah, Ahmet Bilgili, Stefan Eilemann, Henry Markram, Felix Schuermann

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Background: We present a physically-based computational model of the light sheet fluorescence microscope (LSFM). Based on Monte Carlo ray tracing and geometric optics, our method simulates the operational aspects and image formation process of the LSFM. This simulated, in silico LSFM creates synthetic images of digital fluorescent specimens that can resemble those generated by a real LSFM, as opposed to established visualization methods producing visually-plausible images. We also propose an accurate fluorescence rendering model which takes into account the intrinsic characteristics of fluorescent dyes to simulate the light interaction with fluorescent biological specimen. Results: We demonstrate first results of our visualization pipeline to a simplified brain tissue model reconstructed from the somatosensory cortex of a young rat. The modeling aspects of the LSFM units are qualitatively analysed, and the results of the fluorescence model were quantitatively validated against the fluorescence brightness equation and characteristic emission spectra of different fluorescent dyes. AMS subject classification: Modelling and simulation.
Original languageEnglish (US)
JournalBMC BIOINFORMATICS
Volume16
Issue numberS11
DOIs
StatePublished - Aug 13 2015
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2022-05-26
Acknowledgements: This publication was supported in part by the Blue Brain Project (BBP), the Swiss National Science Foundation under Grant 200020-129525 and the King Abdullah University of Science and Technology (KAUST) through the KAUSTEPFL alliance for Neuro-Inspired High Performance Computing.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computer Science Applications

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