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The annotation of cellular nuclei in images of tissue sections is a time consuming but crucial task in quantitative microscopy. We present a machine learning framework incorporating expert knowledge enabling biologists to annotate a large number of nuclear images in a reasonable time. The proposed system is designed to generate three successive levels of annotation, each presenting more details until...
In order to evaluate automated image annotation and object recognition algorithms, ground truth in the form of a set of images correctly annotated with text describing each image is required. In this paper, three image annotation approaches are reviewed: free text annotation, keyword annotation and annotation based on ontologies. The practical aspects of image annotation are then considered. We discuss...
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