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Predicting Segmentation Accuracy for Biological Cell Images

Published

Author(s)

Adele P. Peskin, Alden A. Dima, Joe Chalfoun, John T. Elliott

Abstract

We have performed segmentation procedures on a large number of images from two mammalian cell lines that were seeded at low density, in order to study trends in the segmentation results and make predictions about cellular features that affect segmentation accuracy. By comparing segmentation results from approximately 40000 cells, we find a linear relationship between the highest segmentation accuracy seen for a given cell and the fraction of pixels in the neighborhood of the edge of that cell. This fraction of pixels is at greatest risk for error when cells are segmented. We call the ratio of the size of this pixel fraction to the size of the cell the extended edge neighborhood and this metric can predict segmentation accuracy of any isolated cell.
Proceedings Title
ISVC 2010
Conference Dates
November 28-December 1, 2010
Conference Location
Las Vegas, NV

Keywords

segmentation, accuracy

Citation

Peskin, A. , Dima, A. , Chalfoun, J. and Elliott, J. (2010), Predicting Segmentation Accuracy for Biological Cell Images, ISVC 2010, Las Vegas, NV (Accessed June 17, 2024)

Issues

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Created December 15, 2010, Updated February 19, 2017