Microtubule Dynamics Classification Using a Statistical Model of the Movement of Outer Tips

A new method is proposed for tracking the dynamics of microtubules. It combines a salient point extraction mechanism for segmenting plus-end tips, a robust tracking method capable of locating the trajectories of a large number of feature points, and a classification algorithm capable of determining if the level of activity of a given microtubule video is typical of that of a treated or a control cell. Our method does not rely on the precise tracking of a single microtubule like many previous works, but instead focuses on the generalized movement of ending tips as a whole, which gives a more statistically reliable interpretation of the movement of microtubules. The proposed algorithm is tested using twenty videos of breast cancer microtubules - ten are treated with Taxol and ten are control. We are able to correctly classify those test videos 85% of the time, which is comparable in accuracy, but uses a less complex algorithm than other algorithms.