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Biophys J, April 1999, p. 2230-2237, Vol. 76, No. 4
Center for Light Microscope Imaging and Biotechnology, *Department of Biological Sciences, and #Biomedical Engineering Program, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213 USA
Scientists wishing to communicate the essential
characteristics of a pattern (such as an immunofluorescence
distribution) currently must make a subjective choice of one or two
images to publish. We therefore developed methods for objectively
choosing a typical image from a set, with emphasis on images from cell biology. The methods involve calculation of numerical features to
describe each image, calculation of similarity between images as a
distance in feature space, and ranking of images by distance from the
center of the feature distribution. Two types of features were
explored, image texture measures and Zernike polynomial moments, and
various distance measures were utilized. Criteria for evaluating methods for assigning typicality were proposed and applied to sets of
images containing more than one pattern. The results indicate the
importance of using distance measures that are insensitive to the
presence of outliers. For collections of images of the distributions of
a lysosomal protein, a Golgi protein, and nuclear DNA, the images
chosen as most typical were in good agreement with the conventional
understanding of organelle morphologies. The methods described here
have been implemented in a web server (http://murphylab.web.cmu.edu/services/TypIC).
Biophys J, April 1999, p. 2230-2237, Vol. 76, No. 4
© 1999 by the Biophysical Society 0006-3495/99/04/2230/08 $2.00
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