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Natl. Acad. Sci. U.S.A."],"published-print":{"date-parts":[[2017,1,10]]},"abstract":"<jats:title>Significance<\/jats:title>\n                  <jats:p>Researchers in many areas of science and engineering gather imaging data consisting of a set of pixel intensities. Quantitative analyses of such data often rely on estimating the positions of objects (e.g., single-particle tracking), and many of the algorithms used promise subpixel precision and accuracy. Here, we introduce a method that can reveal biases in such tracking algorithms and correct the associated errors. An advantage of the method is that it uses only the output of the tracking algorithm without needing knowledge of how it works. We illustrate how the method can solve common problems in single-particle tracking. 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