Scalable Image Analysis for Quantitative Microscopy
Author: Friedrich Preußer
Publisher:
Published: 2023*
Total Pages: 0
ISBN-13:
DOWNLOAD EBOOKEnglische Version: Since the invention of the microscope, microscopy images have generated new insights in biomedical research. While in the past these images were used for illustrative purposes, state-of-the-art microscopy images provide quantitative measurements. Moreover, modern microscopes are capable of autonomously producing large image datasets of increasing complexity, rendering manual analysis inefficient if not infeasible. Thus, extracting biologically relevant information from these datasets requires computational analysis using appropriate algorithms and software. While some analysis methods generalize to different microscope set-ups and types of images, others need to be well tailored to a particular problem. In this work, I present two new methods for automated image analysis of microscopy data. First, Fourier ring correlation-based quality estimation (FRC-QE) is a new metric for automated image quality estimation of 3D fluorescence microscopy acquisitions. I benchmarked the method in the context of evaluating clearing efficiency in human brain organoids. FRC-QE automates image quality control, a task that is often performed manually and thereby represents a bottleneck when scaling image-based experiments to thousand or more images. The method can estimate clearing efficiency across experimental replicates and clearing protocols. It generalizes to different microscopy modalities and efficiently scales to thousands of images. Second, I have developed a new method for behavioral imaging of C. elegans larvae. [...].
