Research Article: Active backlight for automating visual monitoring: An analysis of a lighting control technique for Caenorhabditis elegans cultured on standard Petri plates

Date Published: April 16, 2019

Publisher: Public Library of Science

Author(s): Joan Carles Puchalt, Antonio-José Sánchez-Salmerón, Patricia Martorell Guerola, Salvador Genovés Martínez, Giorgio F Gilestro.

http://doi.org/10.1371/journal.pone.0215548

Abstract

Lifespan and healthspan machines can undergo C. elegans image segmentation errors due to changes in lighting conditions, which produce non-uniform images. Most C. elegans monitoring machines use backlight techniques based on the transparency of both the container and media. Backlight illumination obtains high-contrast images with dark C. elegans and a bright background. However, changes in illumination or media transparency conditions can produce non-uniform images, which are currently alleviated by image processing techniques. Besides, these machines should avoid C. elegans exposure to light as much as possible because light stresses worms, and can even affect their lifespan, mainly when using (1) long exposure times, (2) high intensities or (3) wavelengths that come close to ultraviolet. However, if short exposure of worms to light is required for visual monitoring, then light can also be used as a movement stimulus. In this paper, an active backlight method is analysed. The proposed method consists of controlling the light intensities and wavelengths of an illumination dots matrix with PID regulators. These regulators adapt illumination to some changing conditions. The experimental results shows that this method simplifies the image segmentation problem because it is able to automatically compensate not only changes in media transparency throughout assay days, but also changes in ambient conditions, such as smooth condensation on the lid and light derivatives of the illumination source during its lifetime. In addition, the strategic application of wavelengths could be adapted for the requirements of each assay. For instance, a specific control strategy has been proposed to minimise stress to worms and trying to stimulate C. elegans movement in lifespan assays.

Partial Text

The tiny nematode worm Caenorhabditis elegans (C. elegans) offers us a window into biology because they allow researchers to track in vivo biological events [1, 2]. The ease with which C. elegans can be grown, manipulated and observed has driven research to new areas.

The homography mapped each texel with the central pixel of its projected area on the image. The reprojection error (RE) was used to measure the calibration quality assessment. RE was defined as the geometric error corresponding to the average image distance, measured in pixels, between a texel point, and its projection according to the calibration model, and its corresponding measured counterpart. The retroprojection errors obtained at different calibrations fell within the 2.50 ± 0.06 pixels interval. According to these calibrated homographies, a texel projected approximately on an area of 6 × 5 pixels on the image when no diffuser was used, as seen in Fig 3A. The intensity on the image caused by texel was maximum in the projected area centre, which is the integration of the three emitted RGB wavelengths (Fig 3B). There were control dead zones between texels, which is why a dark reticular structure is observed in the image (Fig 3A).

First of all, it was important to analyse all the lighting factors that could affect image quality. Sometimes achieving a pure backlight illumination is difficult. We used a box to isolate the system from outside ambient lighting, but part of the light generated by our backlight bounced off on the box walls, with which a small ambient light component inherently appeared. Thus in order to reduce it, it was necessary to cover the interior with materials that were as little reflective as possible. It was proved that by covering the interior with black EVA rubber, ambient light reduced, which increased the contrast between worms and the background. This was verified by analysing the grey levels of worms, which went from 13 low levels to low ones of 0.

 

Source:

http://doi.org/10.1371/journal.pone.0215548

 

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