Quality assurance for the 3D-PLI workflow
Background and Motivation
The Three-dimensional Polarized Light Imaging (3D-PLI) technology is used to capture high resolution images of thin post-mortem brain sections. The 3D-PLI raw data is processed in a complex reconstruction workflow to extract the orientations of the nerve fibers in the brain tissue.
After the slices have been prepared, they need to be stored until further processing can begin. However, over time, the composition of the stored tissue slowly changes. Such changes, as well as variations in the initial measurement quality, would propagate further down the processing pipeline unless identified at a sufficiently early stage. Delay in the identification of such problems can result in significantly more time spent on the processing pipeline, more changes in the tissue composition, as well as inefficient use of the high performance computing resources. It is therefore vital to have quality assurance procedures in place that can help identify issues early on.
Our approach
We have developed tools and algorithms that can detect potentially deficient measurements at an early stage in the workflow, as well as other errors during the execution of the workflow.
Our collaboration partners
This project is being conducted in collaboration with the Fiber Architecture group of the INM-1.
Related projects at the Simulation Laboratory Neuroscience
- Using structure tensor analysis to measure PLI image registration quality
- Using deep neural networks for identification of brain tissue in very high resolution PLI images
- Calibration of 3D-PLI measurements