Estimation of the quasi-static Young's modulus of the eardrum using a pressurization technique.

The quasi-static Young's modulus of the eardrum's pars tensa is an important modeling parameter in computer simulations. Recent developments in indentation testing and inverse modeling allow estimation of this parameter with the eardrum in situ. These approaches are challenging because of the curved shape of the pars tensa which requires special care during experimentation to keep the indenter perpendicular to the local surface at the point of contact. Moreover, they involve complicated contact modeling. An alternative computer-based method is presented here in which pressurization is used instead of indentation. The Young's modulus of a thin-shell model of the eardrum with subject-specific geometry is numerically optimized such that simulated pressurized shapes match measured counterparts. The technique was evaluated on six healthy rat eardrums, resulting in a Young's modulus estimate of 22.8±1.5MPa. This is comparable to values estimated using indentation testing. The new pressurization-based approach is simpler to use than the indentation-based method for the two reasons noted above.

Motion flow analysis in cell videos using a multi-level clustering method.

Analyzing motion flow of cells is an important task for many biomedical applications. It is a challenging problem due to noise in images and uncontrolled motion of cells. In this study, a method to find regions of organized motion and direction of flow is proposed. Since dense optical flow methods might fail due to homogeneous regions and irregular motion patterns, the technique involves analyzing trajectories of strong corner features. Trajectories are clustered to find dominant flow patterns for different regions of the frame, where a multilevel clustering scheme is followed. Experiments show that the technique gives accurate results for detecting region and direction of flow.