Fertility - Objective semen characterization
Scientists in livestock industries, fertility clinics, and academic research laboratories need to generate correct cell trajectories, count the number of viable cells, and characterize motion in detail using descriptors such as displacement effectiveness or orientation entropy. The demonstration illustrates the process of cell tracking, as well as a subset of the possible analyses.
Characterization of colloid solutions - diffusion coefficient
Colloids are of interest to a number of industries including paints, food, nanotechnologies, and the environment. It is possible to track thousands of colloid particles rapidly and reliably and deliver statistical descriptors for their motion. The demonstration illustrate the process of calculating the diffusion coefficient for a dense colloidal solution, which is related to the size distribution of particles.
Surface science - adatom mobility
Measuring the motion of adatoms over chemically clean surfaces is very informative of the energy landscape and the electronic states in play. In this demonstration, cobalt atom are seen diffusing over a silver surface. They can gain or loose an electron, which has a dramatic effect on their mobility and is manifested as sudden intensity switches. Contributed by Prof. Harald Brune, EPFL.
Protein trafficking
Increasingly, 4D datasets are required in biological imaging to learn more about the motion of proteins and organelles in relation to cell function. This demonstration illustrates the tracking process on a representative biological data set.
Super-resolution tracking.
Super-resolution tracking is the ability to measure position and motion with accuracy better than would be expected, either from consideration of pixel size or from the diffraction limit. By exploiting a-priori knowledge as encoded in mathematical models, it is possible to achieve astonishing precisions. One can fit Gaussian intensity profiles over spots to find their centre with sub-pixel precision. In some applications, it is possible to reach a precision better than 1/100 of a pixel. In this demonstration we illustrate the methodology on a simulated data of spots moving on sine tracks.
Manual tracking of fluorescent speckles
Manual tracking is sometimes useful, for example in order to establish a particular tracking methodology. In this demonstration, we illustrate the manual tracking process for fluorescent speckles in the lamellipodium of migrating cells.
Resolving motion correspondence for densely moving objects
Tracking a few well defined objects distant from each other is relatively elementary. Unfortunately, this situation occurs rarely in meaningful applications. For example, in biological imaging or in granular flows, scenes tend to be crowded, with significant changes occurring between images. In this demonstration, we show how to deal with a difficult sequence from the litterature, using only pairs of successive images and no a priori information. Contributed by Veenman et al. PAMI, vol. 23, No. 1, Jan. 2001.
Tracking demagnetisation grids for cardiology under Magnetic Resonance Imaging (MRI)
Using complex pulse sequences in magnetic resonance imaging, physicians at the Imperial College London are able to generate transient demagnetization grids, thus providing an opportunity for characterizing heart motions in detail via object tracking as shown in the demonstration. Flow movies in particular are used to reveal the average local direction and speed of motion everywhere in the organ over time. Contributed by Dr Protti A., Dr Arridge M., Dr. Gsell W, Biological Imaging Centre,Clinical Sciences Centre, MRC.
Tracking adenovirus particles using fluorescence microscopy
Virologists are among the most assidious users of dynamic imaging. No other technique can offer a more direct window into how these viruses move into and out of cells. Viruses are extremely small and obtaining a useful signal from them is relatively difficult, not to mention photostability issues that decrease their visibility over time. The demonstration shows how to set image analysis parameters to trace virus particles over a large number of frames. Contributed by Prof. Urs Greber, Uni Zuerich.
