Abstract
Mitochondria are dynamic organelles that in most cells behave as a dynamic network and can change their biogenesis and structure depending on the cell needs or as a response to different conditions. Analyzing the architecture of mitochondria is determinant to describe their state and function. In this chapter, image processing techniques are applied in a workflow manner to segment the mitochondrial network and extract the most relevant parameters that enable an accurate morphology analysis. This workflow is programmed with ImageJ macro language and can be applied to automatically analyze multiple cells from multiple images or tiles. When combined with multiwell plates and automated microscopy, this method may allow to perform high content image analysis of hundreds of cells under different conditions.
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Acknowledgments
Authors would like to thank Elisenda Coll from the Advanced Optical Microscopy Facility from CCiTUB from the University of Barcelona for her help in reviewing the manuscript and preparation of samples; Dra. Silvia Ginés and Laura Lopez Molina from Biomedical Science Dept., Institut de Neurociències from the University of Barcelona and IDIBAPS (in collaboration with Movement Disorder Unit from Hospital Santa Creu i Sant Pau, Barcelona); and Dra. Glòria Garrabou and Dr. Francesc Cardellach from Muscle research and mitochondrial function Unit from Cellex- IDIBAPS, CIBERER, Internal Medicine Dept. Hospital Clínic Barcelona School of Medicine-Universitat de Barcelona for providing samples and images.
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Bosch, A., Calvo, M. (2019). Automated Quantitative Analysis of Mitochondrial Morphology. In: Rebollo, E., Bosch, M. (eds) Computer Optimized Microscopy. Methods in Molecular Biology, vol 2040. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9686-5_6
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DOI: https://doi.org/10.1007/978-1-4939-9686-5_6
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