@inbook{27f3a4bc8780437fa6978f745e4bd169,
title = "NanoIndentation, an ImageJ Plugin for the Quantification of Cell Mechanics",
abstract = "Growth and morphogenesis in plants depend on cell wall mechanics and on turgor pressure. Nanoindentation methods, such as atomic force microscopy (AFM), enable measurements of mechanical properties of a tissue at subcellular resolution, while confocal microscopy of tissues expressing fluorescent reporters indicates cell identity. Associating mechanical data with specific cells is essential to reveal the links between cell identity and cell mechanics. Here we describe an image analysis protocol that allows us to segment AFM scans containing information on tissue topography and/or mechanics, to stitch several scans in order to reconstitute an entire region of the tissue investigated, to segment the scans and label cells, and to associate labeled cells to the projection of confocal images. Thus all mechanical data can be mapped to the corresponding cells and to their identity. This protocol is implemented using NanoIndentation, a plugin that we are developing in the Fiji distribution of ImageJ.",
keywords = "Atomic force microscopy, Confocal microscopy, Epifluorescence, Fiji, Image analysis, ImageJ, Mechanical image, Nanoindentation, Segmentation, Stitching, Topographic image, Turgor pressure, Young{\textquoteright}s modulus",
author = "Vincent Mirabet and Nelly Dubrulle and L{\'e}a Rambaud and L{\'e}na Beauzamy and Mathilde Dumond and Yuchen Long and Pascale Milani and Arezki Boudaoud",
note = "Publisher Copyright: {\textcopyright} 2022, Springer Science+Business Media, LLC, part of Springer Nature.",
year = "2022",
month = jan,
day = "1",
doi = "10.1007/978-1-0716-1816-5\_6",
language = "English",
series = "Methods in Molecular Biology",
publisher = "Humana Press Inc.",
pages = "97--106",
booktitle = "Methods in Molecular Biology",
}