Measuring the average cell size and width of its distribution in cellular tissues using Fourier Transform

TL;DR

This paper introduces a Fourier-based automated method for measuring average cell size and distribution in 3D tissues, demonstrating high accuracy with minimal imaging data, suitable for live tissue analysis.

Contribution

The study develops and validates a Fourier transform technique for rapid, accurate cell size measurement in 3D tissues, optimizing imaging parameters for in vivo applications.

Findings

Accurate measurements achievable with as few as 3x3x3 cells in view.

Reduced z-resolution still maintains less than 5% error in size estimation.

Method reduces photobleaching and phototoxicity in live tissue imaging.

Abstract

We present an in-depth investigation of a fully automated Fourier-based analysis to determine the cell size and the width of its distribution in 3D biological tissues. The results are thoroughly tested using generated images, and we offer valuable criteria for image acquisition settings to optimize accuracy. We demonstrate that the most important parameter is the number of cells in the field of view, and we show that accurate measurements can already be made on volume only containing 3x3x3 cells. The resolution in $z$ is also not so important and a reduced number of in-depth images, of order of one per cell, already provides a measure of the mean cell size with less than 5\% error. The technique thus appears to be a very promising tool for very fast live local volume cell measurement in 3D tissues \textit{in vivo} while strongly limiting photobleaching and phototoxicity issues.