Computational image analysis for microscopy (by Adrienne Roeder).

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ID: 60269
2019
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Abstract
plantcell;31/10/tpc.119.tt0819/FIG1F1fig1The age of big data includes sophisticated imaging datasets. Computational image processing is essential for extracting quantitative information from these large image datasets. Computer scientists have been working for decades to build image analysis tools. It is critical for biologists to understand the concepts in image processing so that they can communicate with computer scientists in designing image processing pipelines and applying these tools to their own images. We focus on microscopy images, but the principles apply to other types of images as well. Furthermore, it is important to understand what manipulations are appropriate in preparing images for publication, what manipulations must be disclosed in the methods and the figure legends, and what manipulations are unacceptable. Here we introduce computational image analysis concepts and terms and illustrate them with Fiji and the COSTANZA (COnfocal STack ANalyZer) plugin. We provide a step by step, hands-on workshop with a sample image so that students can try some of these functions themselves.(Posted September xx, 2019)Click HERE to access Teaching Tool ComponentsRECOMMENDED CITATION STYLE:Roeder, A. (September xx, 2019). Computational image analysis for microscopy. Teaching Tools in Plant Biology. The Plant Cell doi/ 10.1105/tpc.119.tt0819.
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Authors
Journal The Plant cell
Year 2019
DOI
tpc.119.tt0819
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Keywords
family members informed consent mental capacity older people proxy decision-making qualitative research

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