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. 2015 Jul;26(2):37-44.
doi: 10.7171/jbt.15-2602-001.

A Quantitative Measure of Field Illumination

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A Quantitative Measure of Field Illumination

Claire M Brown et al. J Biomol Tech. 2015 Jul.

Abstract

In this paper, we describe a statistically based algorithm to quantify the uniformity of illumination in an optical light microscopy imaging system that outputs a single quality factor (QF) score. The importance of homogeneous field illumination in quantitative light microscopy is well understood and often checked. However, there is currently no standard automatic quantitative measure of the uniformity of the field illumination. Images from 89 different laser-scanning confocal microscopes (LSCMs), which were collected as part of an international study on microscope quality assessment, were used as a "training" set to build the algorithm. To validate the algorithm and verify its robustness, images from 33 additional microscopes, including LSCM and wide-field (WF) microscopes, were used. The statistical paradigm used for developing the quality scoring scale was a regression approach to supervised learning. Three intensity profiles across each image-2 corner-to-corner diagonals and a center horizontal-were used to generate pixel-intensity data. All of the lines passed through the center of the image. The intensity profile data then were converted into a single-field illumination QF score in the range of 0-100, with 0 having extreme variation, and therefore, essentially unusable, and 100 having no deviation, i.e., straight lines with a constant uniform intensity. Empirically, a QF ≥ 83 was determined to be the minimum acceptable value based on manufacturer acceptance tests and reasonably achievable values. This new QF is an invaluable metric to ascertain objectively and easily the uniformity of illumination quality, provide a traceable reference for monitoring field uniformity over time, and make a direct comparison among different microscopes. The QF can also be used as an indicator of system failure and the need for alignment or service of the instrument.

Keywords: alignment; flat field; imaging; quality assessment; supervised learning.

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Figures

Figure 1
Figure 1
Photograph of the adjustable fiberoptic microscope coupler with salient parts labeled.
Figure 2
Figure 2
Assembly drawing of the adjustable fiberoptic coupler. The device is green, dimensions are black, hidden lines are blue, centers are red, and tapped holes are purple. All dimensions are in millimeters. Part numbers are from MSC Industrial Supply (Melville, NY, USA; MSCdirect.com); substitution from other suppliers is also possible. OD, outer diameter.
Figure 3
Figure 3
Plotted intensity data and the line segments [upper left to lower right (red); upper right to lower left (blue); and a center horizontal line (yellow)] for Microscope D. This scope exhibited increased illumination on the left, more stable central illumination, and decreasing illumination on the right. Also on the right, the yellow scan displays an apparent discontinuity. Each scan has been approximated by 3 optimally determined line segments whose slopes are used in the scoring function.
Figure 4
Figure 4
Plotted intensity data and the line segments [upper left to lower right (red); upper right to lower left (blue); and a center horizontal line (yellow)] for Microscope AM (see Supplemental Data for more information on this scope), exhibiting a quasiparabolic illumination profile and demonstrating the fit of the 3 line-segment approximations.
Figure 5
Figure 5
Agreement between expert rankings and quality-score percentages (blue circles), showing the relationship is linear (dashed black line). The quality-score percentages were transformed from regression estimates of a score function, in which agreement with expert rankings was achieved only after down-weighting high-ranked scopes (red line; Eq. 2 in Supplemental Data).

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