Texture-Based Segmentation and a New Cell Shape Index for Quantitative Analysis of Cell Spreading in AFM Images

Abstract

A new cell shape index is defined for use with atomic force microscopy height images of cell cultures. The new cell shape index reveals quantitative cell spreading information not included in a conventional cell shape index. A supervised learning-based cell segmentation algorithm was implemented by texture feature extraction and a multi-layer neural network classifier. The texture feature sets for four different culture surfaces were determined from the gray level co-occurrence matrix and local statistics texture models using two feature selection algorithms and by considering computational cost. The quantitative morphometry of quiescent-like and reactive-like cerebral cortical astrocytes cultured on four different culture environments was investigated using the new and conventional cell shape index. Inclusion of cell spreading with stellation information through use of the new cell shape index was shown to change biomedical conclusions derived from conventional cell shape analysis based on stellation alone. The new CSI results showed that the quantitative astrocyte spreading and stellation behavior was induced by both the underlying substrate and the immunoreactivity of the astrocytes