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New microscopic image sequence‐driven cell deformation model
Author(s) -
He Fuyun,
Jiang F.,
Jiang Yanyan,
Ling Sai Ho
Publication year - 2018
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.8281
Subject(s) - deformation (meteorology) , sequence (biology) , computer science , artificial intelligence , biological system , pattern recognition (psychology) , physics , biology , genetics , meteorology
It is of great significance that making quantitative description and analysis of the cell morphological change to explore physiological or pathological status of the life. To achieve the cells morphological changes of quantitative description, the authors constructed a cell deformation model based on microscopic image sequence here. Based on the graph regularisation and structured matrix decomposition, the high‐dimensional shape space is represented by the linear combination of the low‐dimension subshape space, so that the authors get a quantitative indicator which represents the degree of cell deformation–deformation factor. In order to verify the validity of the authors’ model, a deformation feature extraction experiment was performed on three groups of stem cell image sequence with different deformation degree. Compared with other three common quantitative methods of deformation, the authors’ model describes the cell morphological changes more comprehensively, and has better adaptability and stability for describing the diversity of cell movements.