Quantification of Actin Structures Using Unsupervised Pattern Analysis Techniques

The analysis of F-actin organization in cells is a key topic in many fields of biomedical research. While standard protocols for imaging immunostained actin are well established, assessment of the resulting microscopy images is most of the time still performed manually and with a high degree of subjectivity. In this paper, we present a new approach for the analysis of actin structures in microscopy images and the quantification of differences and similarities in actin organization between cells. Compared to existing methods, our approach does not require any previous knowledge about the cells or structures to be analyzed. It works in an unsupervised fashion, combining statistical texture measures and clustering techniques. By this, our method yields large flexibility and allows for application in a wide range of experimental scenarios, and also to heterogeneous cell populations. Experimental evaluation on sample data proves that our method yields meaningful results for biomedical investigations.