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A confident scale–space shape representation framework for cell migration detection
Author(s) -
ZHANG K.,
XIONG H.,
ZHOU X.,
YANG L.,
WANG Y.L.,
WONG S. T. C.
Publication year - 2008
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/j.1365-2818.2008.02050.x
Subject(s) - computer science , segmentation , maxima and minima , algorithm , context (archaeology) , noise (video) , boundary (topology) , representation (politics) , interpolation (computer graphics) , extrapolation , image segmentation , artificial intelligence , computer vision , mathematical optimization , mathematics , image (mathematics) , mathematical analysis , paleontology , politics , political science , law , biology
Summary Automated segmentation of time‐lapse images is a method to facilitate the understanding of the intricate biological progression, e.g. cancer cell migration. To address this problem, we introduce a shape representation enhancement over popular snake models in the context of confident scale–space such that a higher level of interpretation can hopefully be achieved. Our proposed system consists of a hierarchical analytic framework including feedback loops, self‐adaptive and demand‐adaptive adjustment, incorporating a steerable boundary detail term constraint based on multiscale B‐spline interpolation. To minimize the noise interference inherited from microscopy acquisition, the coarse boundary derived from the initial segmentation with refined watershed line is coupled with microscopy compensation using the mean shift filtering. A progressive approximation is applied to achieve represented as a balance between a relief function of watershed algorithm and local minima concerning multiscale optimality, convergence and robust constraints. Experimental results show that the proposed method overcomes problems with spurious branches, arbitrary gaps, low contrast boundaries and low signal‐to‐noise ratio. The proposed system has the potential to serve as an automated data processing tool for cell migration applications.