We have used Quantum dots (QD) bioconjugated with Transferrin (Tf) as targeted luminescent probes to label pancreatic cancer cells, and have employed a confocal microscope to localize the distribution and track the dynamics of QD-Tf nanocomplexes. In this paper, we present our recent results on QD-Tf tracking and vesicle imaging, including quasi-real-time visualization of QD-Tf transport inside cells using a tracking algorithm. This work demonstrates that we have a potentially useful method for discovering the molecular delivery mechanism inside living cells by utilizing the QDs bioconjugates in combination with our tracking algorithm.

The emergence of new microscopy techniques in combination with the increasing resource of bioimaging data has given fresh impetus to utilizing image processing methods for studying biological processes. Cell tracking studies in particular, which are important for a wide range of biological processes such as embryonic development or the immune system, have recently become the focus of attention. These studies typically produce large volumes of data that are hard to investigate manually and therefore call for an automated approach. Due to the large variety of biological cells and the inhomogeneity of applications, however, there exists no widely accepted method or system for cell tracking until today. In this article, we present our publicly available DYNAMIK software environment that allows users to compute a suit of cell features and plot the trajectory of multiple cells over a sequence of frames. Using chemotaxis and Ras pathways as an example, we show how users can employ our software to compute statistics about cell motility and other cell information, and how to evaluate their test series based on the data computed. We see that DYNAMIK's segmentation and tracking compares favorably with the output produced by other software packages.