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Updated: Aug 26, 2025

An Unbiased Approach of Sampling TEM Sections in Neuroscience

An Unbiased Approach of Sampling TEM Sections in Neuroscience

Published on: April 13, 2019

Optimizing sampling for surface localization in 3D-scanning microscopy.

Marie-Anne Burcklen, Frédéric Galland, Loïc Le Goff

Journal of the Optical Society of America. A, Optics, Image Science, and Vision

|October 10, 2022

Summary

This summary is machine-generated.

This study optimizes 3D-scanning fluorescence imaging for living tissues by minimizing light exposure. It develops a method using the Cramér-Rao bound to determine optimal scanning strategies for biological surface estimation.

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Last Updated: Aug 26, 2025

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Published on: October 29, 2019

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Published on: May 12, 2019

Area of Science:

Biomedical optics
Fluorescence imaging
Computational imaging

Background:

3D-scanning fluorescence imaging of living tissue requires reduced phototoxicity.
Adaptive and sparse scanning schemes minimize light dose by focusing on biological surfaces.
Estimating biological surface position with a Gaussian intensity profile is crucial.

Purpose of the Study:

To optimize 3D-scanning fluorescence imaging acquisition schemes under a constant photon budget.
To develop a method for determining optimal scanning point positions and numbers for biological surface estimation.
To define quasi-optimal acquisition strategies with and without prior knowledge of surface location.

Main Methods:

Utilizing the Cramér-Rao bound for optimization.
Modeling biological surface intensity profiles as Gaussian shapes.
Assuming signal-dependent Gaussian noise in the imaging process.

Main Results:

Developed an approach to optimize scanning point positions and numbers for efficient 3D fluorescence imaging.
Demonstrated that the optimization problem simplifies to a few parameters for regular sampling.
Defined quasi-optimal acquisition strategies applicable with and without prior surface location knowledge.

Conclusions:

The proposed Cramér-Rao bound-based method enables efficient 3D-scanning fluorescence imaging with reduced phototoxicity.
Optimized scanning strategies enhance biological surface position estimation accuracy under limited photon budgets.
This work provides a framework for developing advanced, low-light 3D imaging techniques for live tissues.