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Segmentation in Bioimaging

Abstract : This chapter surveys basic segmentation techniques and point to tools that make them accessible in practical situations. Segmentation is very often the first step when doing quantification. Other image analysis techniques, such as pixel‐based co‐localisation, optical flow, etc. are not based on segmentation, yet offer useful information condensation that can lead to a proper scientific conclusion. The chapter focuses on the list of integers that comprises an image. Automatic counting of objects is almost always done on images where objects appear bright over a dark background, ideally flat. The set of connected pixels with a shared identity forms an object, from which a contour can be extracted and quantification performed. The chapter focuses on what quantifiable information is required to reach a scientific conclusion, pick an analysing technique that can yield it, find or write a software tool that implements it, and finally acquire images that can be analysed with such a tool.
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Contributor : Jean-Yves Tinevez Connect in order to contact the contributor
Submitted on : Tuesday, May 26, 2020 - 10:54:31 AM
Last modification on : Thursday, April 7, 2022 - 10:10:40 AM




Jean-Yves Tinevez. Segmentation in Bioimaging. Ann Wheeler; Ricardo Henriques. Standard and Super-Resolution Bioimaging Data Analysis, John Wiley & Sons, Ltd, pp.47-81, 2017, 9781119096900. ⟨10.1002/9781119096948.ch3⟩. ⟨pasteur-02624210⟩



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