Near real time ETEM streaming video analysis

The Environmental Transmission Electron Microscopy (ETEM) provides a powerful tool to observe the formation and evolution of nano-particles over time. However, ETEM generates extremely large amounts of data at level of 3GB/s, which impossible to be analyzed by manually processing or even by using a single PC. Moreover, the image stream obtained from the ETEM is very noisy. In this project, our goal is automatically analyze the physical characteristics of the nanoparticles. We proposed an approach that detect the nano-particles in each frame, and then track all the nano-particles over time, finally we can analyze the dynamical physical characteristics of the nano-particles, such as merging, absorbing, size and distance change over time. Specifically, our proposed approach detects the nano-particles in each frame independently, which could be highly parallelized. The experimental results show the proposed model could detect and track nano-particles robustly.