title: Digital image analysis of self-similar cell profiles.
abstract: Many biological objects appear to have self-similar structures which can be characterized by their fractal dimension D. However, applications of the concept of fractal geometry are rather scarce in cell and tissue biology. Here we adapt and analyse critically 3 methods of digital image analysis to measure D of cellular profiles. As prototype examples we investigate in detail 2 samples of cells: (i) human T-lymphocytes from normal donors, and (ii) hairy leukemic cells. It is shown that D correlates to the structural complexity of the individual cell contour. The calculated D values for cells out of the same cell line scatter around a mean value D = 1.15 for T-lymphocytes (S.D. = 0.03) and D = 1.34 for hairy leukemic cells (S.D. = 0.04). Consequently, we interprete D as a statistical measure for the sample's fractal dimension.
authors.affiliation: Abteilung für Mathematische Physik, Universität Ulm, Germany.
authors.forename: T F
authors.initials: TF
authors.lastname: Nonnenmacher
authors.forename: G
authors.initials: G
authors.lastname: Baumann
authors.forename: A
authors.initials: A
authors.lastname: Barth
authors.forename: G A
authors.initials: GA
authors.lastname: Losa
mesh_terms: D005434:Flow Cytometry; D017709:Fractals; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007943:Leukemia, Hairy Cell / Q000473:pathology*; D008854:Microscopy, Electron; D013601:T-Lymphocytes / Q000648:ultrastructure*