Abstract
This paper presents a geometric method for modeling dynamic features of cells in image sequences. The morphological changes in cellular membrane boundaries are represented as sequences of parameterized contours. These sequences are analyzed as paths on a shape space equipped with an invariant metric, and matched using dynamic time warping. Experimental results show high sensitivity of the proposed dynamic features to the morphological changes observed in lymphocytes of healthy mice after undergoing skin transplantation when compared with standard representation methods and shape features.
Cite
CITATION STYLE
An, X., Liu, Z., Shi, Y., Li, N., Wang, Y., & Joshi, S. H. (2012). Modeling dynamic cellular morphology in images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7510 LNCS, pp. 340–347). Springer Verlag. https://doi.org/10.1007/978-3-642-33415-3_42
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