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J Microsc. 2007 Aug;227(Pt 2):140-56.

Comparison of quantitative methods for cell-shape analysis.

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1
Program in Biomedical Informatics, and Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA.

Abstract

Morphology is an important large-scale manifestation of the global organizational and physiological state of cells, and is commonly used as a qualitative or quantitative measure of the outcome of various assays. Here we evaluate several different basic representations of cell shape - binary masks, distance maps and polygonal outlines - and different subsequent encodings of those representations - Fourier and Zernike decompositions, and the principal and independent components analyses - to determine which are best at capturing biologically important shape variation. We find that principal components analysis of two-dimensional shapes represented as outlines provide measures of morphology which are quantitative, biologically meaningful, human interpretable and work well across a range of cell types and parameter settings.

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