Using structure tensor analysis to measure PLI image registration quality
Background and Motivation
The Three-dimensional Polarized Light Imaging (3D-PLI) technology is used to capture high resolution images of thinly sliced sections of post-mortem brains. These images can then be stacked to reconstruct the brain in three dimensions.
After the aforementioned 3D reconstruction has been performed, its quality needs to be checked. This cannot be done by eye because of the amount of sections on the one hand, and small differences caused by slightly different parameter-sets which are not detectable by eye on the other hand.
Our approach
Since the registered stack of slices should be a much smoother image, Structure Tensor Analysis (STA) can be used to determine its quality.
STA builds a matrix for each pixel, summarizing the predominant directions of pixel intensity gradients in its neighborhood. The energy value, i.e., the root of the sum of squared eigenvalues, of these matrices can be used as a measure of registration quality because low gradients result in low energy and vice versa.
In addition to being involved in algorithm design, implementation, and data analysis, we are also actively developing software tools that can be used by researchers to perform STA with limited programming effort.
Our collaboration partners
This project is being conducted in collaboration with the Fiber Architecture group of the INM-1.
Related projects at Simulation Laboratory Neuroscience
- Using deep neural networks for identification of brain tissue in very high resolution PLI images
- Quality assurance for the 3D-PLI workflow
- Calibration of 3D-PLI measurements