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**Authors:** Jean-Karim Heriche, Coralie Muller
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In many bioimaging projects, image analysis produces quantitative descriptions of biological characteristics. These quantitative descriptions often take the form of numerical features associated with the images and regions of interest (ROIs, e.g. segmented objects) on those images. Examples of such features are mean intensity of a fluorescent marker and area it occupies. Plotting these features is often used to identify groups or outliers. However, it is sometimes difficult to associate abstract features to visual characteristics of the objects they describe. Typical questions that arise in this context are:
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In many bioimaging projects, image analysis produces quantitative descriptions of biological characteristics. These quantitative descriptions often take the form of numerical features associated with the images and regions of interest (ROIs, e.g. segmented objects) on those images. Examples of such features are mean intensity of a fluorescent marker and area it occupies. Plotting these features is often used to identify groups or outliers. However, it is sometimes difficult to associate abstract features with visual characteristics of the objects they describe. Typical questions that arise in this context are:
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- are there features that can separate different groups?
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- what do members of different groups look like?
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- what do outliers look like?
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