Title :
Automatic segmentation of focal adhesions from mouse embryonic fibroblasts
Author :
Reyes-Aldasoro, Constantino Carlos ; Barri, Muruj ; Hafezparast, Majid
Author_Institution :
Biomed. Eng. Res. Centre, City Univ. London, London, UK
Abstract :
This work describes an automatic algorithm for the segmentation and quantification of focal adhesions from mouse embryonic fibroblasts. The main challenges solved by this algorithm are: the variability of the intensity of the focal adhesions, the detection of an outer ring, which distinguishes the cell periphery responsible for the cell migration, and the quantification of the characteristics of the focal adhesions. The algorithm detects maximal regions through gradients and uses a region-growing algorithm limited by intensity-based edges. The outer ring is calculated based on the average radial intensity from an extended centroid of the cell. Finally, traditional morphological characteristics are obtained to distinguish between two groups of cells. Two of the measurements employed showed statistical difference between two groups of cells.
Keywords :
adhesion; biomechanics; biomedical optical imaging; cell motility; edge detection; image segmentation; medical image processing; automatic focal adhesion segmentation; cell migration; intensity-based edges; morphological characteristics; mouse embryonic fibroblasts; region-growing algorithm; statistical analysis; Adhesives; Algorithm design and analysis; Fibroblasts; Image edge detection; Mice; Recruitment; Shape; MEF; cell segmentation; focal adhesions; mouse embryonic fibroblasts;
Conference_Titel :
Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on
Conference_Location :
New York, NY
DOI :
10.1109/ISBI.2015.7163932