Fast, High Acuity Imaging and AI-assisted Analysis

Clear imaging of whole-mounted mouse retina with THUNDER and Aivia

Mouse whole-mount retina. Image courtesy of the Experimental Ophthalmology Group, University of Murcia, Spain. Mouse_whole-mount_retina_Thundered.jpg

In this article, we demonstrate how imaging the whole-mounted mouse retina using THUNDER can dramatically boost the speed and quality of data collection. Compared to conventional widefield microscopy, THUNDER imaging provides sharper images and allows for rapid segmentation without out-of-focus blur or haze. Combined with Aivia, this allows high-powered, efficient analysis of images, with high quality and reproducible results between samples.

The challenges with out-of-focus blur and long acquisition times

In conventional widefield imaging, a common issue is out-of-focus blur, especially when imaging thick sections or whole-mounted samples like the retina. Blur is caused by illumination of the whole sample, particularly the areas above and below the image plane. This causes poor contrast of fluorophore channels, masks image information, and reduces the ability for clear and reproducible analysis. Confocal point scanners allow optical sectioning and are the benchmark for superior image quality and high-contrast fluorescence images, even for multicolour data acquisition. However, with confocal point scanners, acquiring image sequences of large samples might be time consuming depending on the scanning speed.

Together, low-throughput acquisition and blur can hamper a scientist’s ability to quantify cellular and molecular features of tissue like the retina. For this type of research, it’s important to have a solution capable of capturing images with high acuity and fast screening of the retina, so 3D reconstruction can be performed.

Key Learnings

  • High-acuity imaging of whole-mounted retina samples using THUNDER
  • Powerful image analysis of THUNDERed images with Aivia
  • Better quality and reproducible analysis of thick tissues like the retina

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