Modeling and Classifying Tip Dynamics of Growing Cells in Video
| Autor: | Asongu L. Tambo, Bir Bhanu |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
tip growth classification
0301 basic medicine Artificial Intelligence and Image Processing Computer science Gaussian Feature extraction Measure (mathematics) Cell wall 03 medical and health sciences symbols.namesake Feature (machine learning) Computer vision Electrical and Electronic Engineering tip growth features Communications Technologies business.industry Applied Mathematics Process (computing) Image segmentation 030104 developmental biology Signal Processing symbols Tip growth Artificial intelligence Networking & Telecommunications Biological system business |
| Zdroj: | IEEE SIGNAL PROCESSING LETTERS, vol 23, iss 10 IEEE Signal Processing Letters, vol 23, iss 10 |
| ISSN: | 1558-2361 1070-9908 |
| DOI: | 10.1109/lsp.2016.2598558 |
| Popis: | Plant biologists study pollen tubes to discover the functions of many proteins/ions and map the complex network of pathways that lead to an observable growth behavior. Many growth models have been proposed that address parts of the growth process: internal dynamics and cell wall dynamics, but they do not distinguish between the two types of growth segments: straight versus turning behavior. We propose a method of classifying segments of experimental videos by extracting features from the growth process during each interval. We use a stress–strain relationship to measure the extensibility in the tip region. A biologically relevant three-component Gaussian is used to model spatial distribution of tip extensibility and a second-order damping system is used to explain the temporal dynamics. Feature-based classification shows that the location of maximum tip extensibility is the most distinguishing feature between straight versus turning behavior. |
| Databáze: | OpenAIRE |
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