A Real-time Multiple-cell Tracking Platform for Dielectrophoresis (DEP) based Cellular Analysis,
There is an increasing demand from biosciences to develop new and efficient techniques to assist in the preparation and analysis of biological samples such as cells in suspension. A dielectrophoresis (DEP)-based characterization and measurement technique on biological cells opens up a broader perspective for early diagnosis of diseases. An efficient real-time multiple-cell tracking platform coupled with DEP to capture and quantify the dynamics of cell motion and obtain cell viability information is presented. The procedure for tracking a single DEP-levitated Canola plant protoplast, using the motion-based segmentation algorithm hierarchical adaptive merge split mesh-based technique (HAMSM) for cell identification, has been enhanced for identifying and tracking multiple cells. The tracking technique relies on the deformation of mesh topology that is generated according to the movement of biological cells in a sequence of images that allows the simultaneous extraction of the biological cell from the image and the associated motion characteristics. Preliminary tests were conducted with yeast cells and then applied to a cancerous cell line subjected to DEP fields. Characteristics, such as cell count, velocity and size, were individually extracted from the tracked results of the cell sample. Tests were limited to eight yeast cells and two cancer cells. A performance analysis to assess tracking accuracy, computational effort and processing time was also conducted. The tracking technique employed on model intact cells in DEP fields proved to be accurate, reliable and robust.
Brinda Prasad, K. Kaler and Wael Badawy, “A Real-time Multiple-cell Tracking Platform for Dielectrophoresis (DEP) based Cellular Analysis,” Measurement Science and Technology, Vol. 6, April 2005, pp. 909-924.