Comparison of quantitative methods for cell‐shape analysis

By Zachary Pincus, Julie A. Theriot. Journal of Microscopy, 2007

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3D Cell Nuclear Morphology: Microscopy Imaging Dataset And Voxel-Based Morphometry Classification Results (2017, background): “While many efforts have been made to develop cell and nuclear morphological characteristics in 2D or pseudo-3D [12, 25], several studies have suggested that 3D measures provide better results for nuclear morphometry description and discrimination [6, 21].”
Tracking in cell and developmental biology. (2009, methodology): “For example, variabilities in cell shape (within populations or per cell over time) can be very effectively studied using statistical tools such as principal component analysis (PCA) of the cell outlines [55].”
Data-analysis strategies for image-based cell profiling (2017, background): “This is typically measured as the similarity among the profiles of replicate pairs of the same biological treatment, which should be significantly higher than the similarity to profiles of other experimental conditions (controls and/or other biological treatments).”